diff --git a/.github/workflows/gpu.yml b/.github/workflows/gpu.yml
index c78bd01..8a09cd8 100644
--- a/.github/workflows/gpu.yml
+++ b/.github/workflows/gpu.yml
@@ -33,12 +33,10 @@
 #       run: |
 #         pip install torch==1.11.0+cu115 torchvision==0.12.0+cu115 -f https://download.pytorch.org/whl/torch_stable.html
 #
-#     - name: Install package and test dependencies
+#     - name: Install dependencies
 #       run: |
-#         python -m pip install --upgrade "pip<24.0"
-#         pip install -r requirements.txt
-#         pip install pytest pytest-cov
-#         python setup.py develop
+#         python -m pip install --upgrade pip
+#         pip install -e .
 #
 #     - name: Setup test data
 #       run: |
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 0bc5409..0ce29f0 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -48,12 +48,10 @@ jobs:
       run: |
         pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
 
-    - name: Install package and test dependencies
+    - name: Install dependencies
       run: |
-        python -m pip install --upgrade "pip<24.0"
-        pip install -r requirements.txt
-        pip install pytest pytest-cov
-        python setup.py develop
+        python -m pip install --upgrade pip
+        pip install .
 
     - name: Setup test data
       run: |
diff --git a/README.md b/README.md
index 6bf2032..6637c14 100644
--- a/README.md
+++ b/README.md
@@ -22,9 +22,19 @@ learning research into action detection:
 ## Installation
 For full installation instructions, see [this readme file](docs/installation.md).
 
-In brief:
-* [Install PyTorch](https://pytorch.org/)
-* `pip install deepethogram`
+### Quick Install (Recommended)
+We recommend using [UV](https://docs.astral.sh/uv/) for fast, reliable Python package management:
+
+1. Install UV:
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   ```
+   For troubleshooting or Windows, see [other installation methods](https://docs.astral.sh/uv/getting-started/installation/)
+
+2. Install DeepEthogram:
+   ```bash
+   uv pip install deepethogram
+   ```
 
 ## Data
 **NEW!** All datasets collected and annotated by the DeepEthogram authors are now available from this DropBox link:
@@ -65,7 +75,7 @@ The major dependencies for DeepEthogram are as follows:
 * pytorch, torchvision: all the neural networks, training, and inference pipelines were written in PyTorch
 * pytorch-lightning: for nice model training base classes
 * kornia: for GPU-based image augmentations
-* pyside2: for the GUI
+* PySide6: for the GUI (upgraded from PySide2 in v0.3.0)
 * opencv: for video and image reading and writing
 * opencv_transforms: for fast image augmentation
 * scikit-learn, scipy: for binary classification metrics
diff --git a/deepethogram/gui/custom_widgets.py b/deepethogram/gui/custom_widgets.py
index 339f459..f80931c 100644
--- a/deepethogram/gui/custom_widgets.py
+++ b/deepethogram/gui/custom_widgets.py
@@ -7,8 +7,8 @@
 from typing import Union
 
 import numpy as np
-from PySide2 import QtCore, QtGui, QtWidgets
-from PySide2.QtCore import Signal, Slot
+from PySide6 import QtCore, QtGui, QtWidgets
+from PySide6.QtCore import Signal, Slot
 
 from deepethogram.file_io import VideoReader
 
@@ -19,7 +19,7 @@
 
 
 def numpy_to_qpixmap(image: np.ndarray) -> QtGui.QPixmap:
-    if image.dtype == np.float:
+    if image.dtype == np.float64 or image.dtype == np.float32:
         image = float_to_uint8(image)
     H, W, C = int(image.shape[0]), int(image.shape[1]), int(image.shape[2])
     if C == 4:
@@ -33,7 +33,7 @@ def numpy_to_qpixmap(image: np.ndarray) -> QtGui.QPixmap:
 
 
 def float_to_uint8(image: np.ndarray) -> np.ndarray:
-    if image.dtype == np.float:
+    if image.dtype == np.float64 or image.dtype == np.float32:
         image = (image * 255).clip(min=0, max=255).astype(np.uint8)
     return image
 
@@ -650,7 +650,7 @@ def initialize(
             button = self._make_button(behavior, i)
             self.buttons.append(button)
             layout.addWidget(button, 0, alignment=QtCore.Qt.AlignTop)
-        layout.setMargin(0)
+        layout.setContentsMargins(0, 0, 0, 0)
         layout.setSpacing(0)
         self.layout = layout
         self.setLayout(self.layout)
@@ -788,7 +788,7 @@ def add_behavior(self, behavior: str):
 
         self.label._add_row()
         if i < 10:
-            self.toggle_shortcuts.append(QtWidgets.QShortcut(QtGui.QKeySequence(str(i)), self))
+            self.toggle_shortcuts.append(QtGui.QShortcut(QtGui.QKeySequence(str(i)), self))
         self.toggle_shortcuts[i].activated.connect(self.buttons.buttons[i].click)
 
 
@@ -875,10 +875,10 @@ def __init__(self):
             fixed=False,
         )
 
-        next_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Right"), self)
+        next_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Right"), self)
         next_shortcut.activated.connect(partial(self.label.label.change_view_dx, 1))
         # next_shortcut.activated.connect(partial(self.label.change_view_dx, 1))
-        back_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Left"), self)
+        back_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Left"), self)
         back_shortcut.activated.connect(partial(self.label.label.change_view_dx, -1))
 
         self.setCentralWidget(self.label)
@@ -897,4 +897,4 @@ def sizeHint(self):
     testing.initialize(behaviors=["background", "a", "b", "c", "d", "e"], n_timepoints=15000, debug=True)
     testing.update()
     testing.show()
-    app.exec_()
+    app.exec()
diff --git a/deepethogram/gui/main.py b/deepethogram/gui/main.py
index 0bbb373..8beea3c 100644
--- a/deepethogram/gui/main.py
+++ b/deepethogram/gui/main.py
@@ -9,9 +9,9 @@
 import numpy as np
 import pandas as pd
 from omegaconf import DictConfig, OmegaConf
-from PySide2 import QtCore, QtGui, QtWidgets
-from PySide2.QtCore import Slot
-from PySide2.QtWidgets import QFileDialog, QInputDialog, QMainWindow
+from PySide6 import QtCore, QtGui, QtWidgets
+from PySide6.QtCore import Slot
+from PySide6.QtWidgets import QFileDialog, QInputDialog, QMainWindow
 
 from deepethogram import configuration, projects, utils
 from deepethogram.file_io import VideoReader
@@ -63,37 +63,37 @@ def __init__(self, cfg: DictConfig):
 
         # scroll down to Standard Shorcuts to find what the keys are called:
         # https://doc.qt.io/qt-5/qkeysequence.html
-        next_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Right"), self)
+        next_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Right"), self)
         # partial functions create a new, separate function with certain default arguments
         next_shortcut.activated.connect(partial(self.move_n_frames, 1))
         next_shortcut.activated.connect(self.user_did_something)
 
-        up_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Up"), self)
+        up_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Up"), self)
         up_shortcut.activated.connect(partial(self.move_n_frames, -cfg.vertical_arrow_jump))
         up_shortcut.activated.connect(self.user_did_something)
 
-        down_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Down"), self)
+        down_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Down"), self)
         down_shortcut.activated.connect(partial(self.move_n_frames, cfg.vertical_arrow_jump))
         down_shortcut.activated.connect(self.user_did_something)
 
-        back_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Left"), self)
+        back_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Left"), self)
         back_shortcut.activated.connect(partial(self.move_n_frames, -1))
         back_shortcut.activated.connect(self.user_did_something)
 
-        jumpleft_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Ctrl+Left"), self)
+        jumpleft_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Ctrl+Left"), self)
         jumpleft_shortcut.activated.connect(partial(self.move_n_frames, -cfg.control_arrow_jump))
         jumpleft_shortcut.activated.connect(self.user_did_something)
 
-        jumpright_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Ctrl+Right"), self)
+        jumpright_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Ctrl+Right"), self)
         jumpright_shortcut.activated.connect(partial(self.move_n_frames, cfg.control_arrow_jump))
         jumpright_shortcut.activated.connect(self.user_did_something)
 
         self.ui.actionSave_Project.triggered.connect(self.save)
-        save_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Ctrl+S"), self)
+        save_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Ctrl+S"), self)
         save_shortcut.activated.connect(self.save)
-        finalize_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Ctrl+F"), self)
+        finalize_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Ctrl+F"), self)
         finalize_shortcut.activated.connect(self.finalize)
-        open_shortcut = QtWidgets.QShortcut(QtGui.QKeySequence("Ctrl+O"), self)
+        open_shortcut = QtGui.QShortcut(QtGui.QKeySequence("Ctrl+O"), self)
         open_shortcut.activated.connect(self.load_project)
         self.ui.finalize_labels.clicked.connect(self.finalize)
         self.ui.exportPredictions.clicked.connect(self.export_predictions)
@@ -109,7 +109,7 @@ def __init__(self, cfg: DictConfig):
         self.latent_name = None
         self.thresholds = None
         for i in range(10):
-            self.toggle_shortcuts.append(QtWidgets.QShortcut(QtGui.QKeySequence(str(i)), self))
+            self.toggle_shortcuts.append(QtGui.QShortcut(QtGui.QKeySequence(str(i)), self))
             tmp_func = partial(self.respond_to_keypress, i)
             self.toggle_shortcuts[i].activated.connect(tmp_func)
             self.toggle_shortcuts[i].activated.connect(self.user_did_something)
@@ -394,7 +394,7 @@ def generate_featureextractor_inference_args(self):
             keys.append(key)
             no_outputs.append(record["output"] is None)
         form = ShouldRunInference(keys, no_outputs)
-        ret = form.exec_()
+        ret = form.exec()
         if not ret:
             return
         should_infer = form.get_outputs()
@@ -518,7 +518,7 @@ def generate_sequence_inference_args(self):
             if has_latents[i]:
                 keys_with_features.append(key)
         form = ShouldRunInference(keys_with_features, no_sequence_outputs)
-        ret = form.exec_()
+        ret = form.exec()
         if not ret:
             return
         should_infer = form.get_outputs()
@@ -617,7 +617,7 @@ def run_overnight(self):
 
     def _new_project(self):
         form = CreateProject()
-        ret = form.exec_()
+        ret = form.exec()
         if not ret:
             return
         project_name = form.project_box.text()
@@ -1183,7 +1183,7 @@ def run() -> None:
     window.resize(1024, 768)
     window.show()
 
-    sys.exit(app.exec_())
+    sys.exit(app.exec())
 
 
 def entry() -> None:
diff --git a/deepethogram/gui/mainwindow.py b/deepethogram/gui/mainwindow.py
index fb85094..7a1e931 100644
--- a/deepethogram/gui/mainwindow.py
+++ b/deepethogram/gui/mainwindow.py
@@ -8,7 +8,7 @@
 #
 # WARNING! All changes made in this file will be lost!
 
-from PySide2 import QtCore, QtWidgets
+from PySide6 import QtCore, QtGui, QtWidgets
 
 
 class Ui_MainWindow(object):
@@ -186,41 +186,41 @@ def setupUi(self, MainWindow):
         self.statusBar = QtWidgets.QStatusBar(MainWindow)
         self.statusBar.setObjectName("statusBar")
         MainWindow.setStatusBar(self.statusBar)
-        self.actionNew_Project = QtWidgets.QAction(MainWindow)
+        self.actionNew_Project = QtGui.QAction(MainWindow)
         self.actionNew_Project.setObjectName("actionNew_Project")
-        self.actionSave_Project = QtWidgets.QAction(MainWindow)
+        self.actionSave_Project = QtGui.QAction(MainWindow)
         self.actionSave_Project.setEnabled(False)
         self.actionSave_Project.setObjectName("actionSave_Project")
-        self.actionAdd = QtWidgets.QAction(MainWindow)
+        self.actionAdd = QtGui.QAction(MainWindow)
         self.actionAdd.setEnabled(False)
         self.actionAdd.setObjectName("actionAdd")
-        self.actionRemove = QtWidgets.QAction(MainWindow)
+        self.actionRemove = QtGui.QAction(MainWindow)
         self.actionRemove.setEnabled(False)
         self.actionRemove.setObjectName("actionRemove")
-        self.actionStyle = QtWidgets.QAction(MainWindow)
+        self.actionStyle = QtGui.QAction(MainWindow)
         self.actionStyle.setObjectName("actionStyle")
-        self.actionOpen = QtWidgets.QAction(MainWindow)
+        self.actionOpen = QtGui.QAction(MainWindow)
         self.actionOpen.setEnabled(False)
         self.actionOpen.setObjectName("actionOpen")
-        self.actionEdit_list = QtWidgets.QAction(MainWindow)
+        self.actionEdit_list = QtGui.QAction(MainWindow)
         self.actionEdit_list.setObjectName("actionEdit_list")
-        self.actionNext = QtWidgets.QAction(MainWindow)
+        self.actionNext = QtGui.QAction(MainWindow)
         self.actionNext.setObjectName("actionNext")
-        self.actionPrevious = QtWidgets.QAction(MainWindow)
+        self.actionPrevious = QtGui.QAction(MainWindow)
         self.actionPrevious.setObjectName("actionPrevious")
-        self.actionOpen_Project = QtWidgets.QAction(MainWindow)
+        self.actionOpen_Project = QtGui.QAction(MainWindow)
         self.actionOpen_Project.setObjectName("actionOpen_Project")
-        self.importLabels = QtWidgets.QAction(MainWindow)
+        self.importLabels = QtGui.QAction(MainWindow)
         self.importLabels.setObjectName("importLabels")
-        self.actionAdd_videos = QtWidgets.QAction(MainWindow)
+        self.actionAdd_videos = QtGui.QAction(MainWindow)
         self.actionAdd_videos.setObjectName("actionAdd_videos")
-        self.classifierInference = QtWidgets.QAction(MainWindow)
+        self.classifierInference = QtGui.QAction(MainWindow)
         self.classifierInference.setCheckable(True)
         self.classifierInference.setObjectName("classifierInference")
-        self.actionOvernight = QtWidgets.QAction(MainWindow)
+        self.actionOvernight = QtGui.QAction(MainWindow)
         self.actionOvernight.setCheckable(True)
         self.actionOvernight.setObjectName("actionOvernight")
-        self.actionAdd_multiple = QtWidgets.QAction(MainWindow)
+        self.actionAdd_multiple = QtGui.QAction(MainWindow)
         self.actionAdd_multiple.setObjectName("actionAdd_multiple")
         self.menuDeepEthogram.addAction(self.actionNew_Project)
         self.menuDeepEthogram.addAction(self.actionSave_Project)
diff --git a/deepethogram/gui/menus_and_popups.py b/deepethogram/gui/menus_and_popups.py
index fa57719..9b7b660 100644
--- a/deepethogram/gui/menus_and_popups.py
+++ b/deepethogram/gui/menus_and_popups.py
@@ -1,7 +1,7 @@
 import pathlib
 import warnings
 
-from PySide2 import QtCore, QtWidgets
+from PySide6 import QtCore, QtWidgets
 
 
 def simple_popup_question(parent, message: str):
@@ -25,7 +25,7 @@ def overwrite_or_not(parent):
     )
     overwrite = msgBox.addButton("Overwrite", QtWidgets.QMessageBox.YesRole)
     unlabeled = msgBox.addButton("Only import unlabeled", QtWidgets.QMessageBox.NoRole)
-    msgBox.exec_()
+    msgBox.exec()
     if msgBox.clickedButton() is overwrite:
         return True
     elif msgBox.clickedButton() is unlabeled:
@@ -46,7 +46,7 @@ def __init__(self, parent=None):
         )
         msgBox.addButton(QtWidgets.QPushButton("Overwrite"), QtWidgets.QMessageBox.YesRole)
         msgBox.addButton(QtWidgets.QPushButton("Only import unlabeled"), QtWidgets.QMessageBox.NoRole)
-        msgBox.exec_()
+        msgBox.exec()
 
 
 class CreateProject(QtWidgets.QDialog):
@@ -148,8 +148,8 @@ def get_outputs(self):
     form = ShouldRunInference(
         ["M134_20141203_v001", "M134_20141203_v002", "M134_20141203_v004"] * num, [True, True, False] * num
     )
-    ret = form.exec_()
+    ret = form.exec()
     if ret:
         print(form.get_outputs())
-    # ret = app.exec_()
+    # ret = app.exec()
     # print(ret)
diff --git a/docker/Dockerfile-full b/docker/Dockerfile-full
index d66833a..1b6c062 100644
--- a/docker/Dockerfile-full
+++ b/docker/Dockerfile-full
@@ -31,10 +31,11 @@ RUN curl -sLo ~/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-py39
 
 # install
 RUN conda install python=3.7 -y
-RUN pip install setuptools --upgrade && pip install --upgrade "pip<24.0"
-RUN pip install torch==1.11.0+cu115 torchvision==0.12.0+cu115 -f https://download.pytorch.org/whl/torch_stable.html
-
+RUN pip install --upgrade pip
+# Install deepethogram with dev dependencies
 ADD . /app/deepethogram
 WORKDIR /app/deepethogram
+# Use Python 3.7 compatible pyproject.toml
+RUN cp pyproject_py37.toml pyproject.toml
 ENV DEG_VERSION='full'
-RUN pip install -e .
+RUN pip install -e ".[dev]"
diff --git a/docker/Dockerfile-gui b/docker/Dockerfile-gui
index b8b6487..6dd30d4 100644
--- a/docker/Dockerfile-gui
+++ b/docker/Dockerfile-gui
@@ -35,13 +35,16 @@ RUN curl -sLo ~/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-py39
 
 # install
 RUN conda install python=3.7 -y
-RUN pip install setuptools --upgrade && pip install --upgrade pip
+RUN pip install --upgrade pip
 
 # TODO: REFACTOR CODE SO IT'S POSSIBLE TO RUN GUI WITHOUT TORCH
-RUN conda install pytorch cpuonly -c pytorch
+# Install PyTorch CPU via pip to avoid conda issues with Python 3.7
+RUN pip install torch==1.11.0+cpu torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
 
-# # needed for pandas for some reason
+# Install deepethogram with dev dependencies
 ADD . /app/deepethogram
 WORKDIR /app/deepethogram
+# Use Python 3.7 compatible pyproject.toml
+RUN cp pyproject_py37.toml pyproject.toml
 ENV DEG_VERSION='gui'
-RUN pip install -e .
+RUN pip install -e ".[dev]"
diff --git a/docker/Dockerfile-headless b/docker/Dockerfile-headless
index ce92955..95e7ef0 100644
--- a/docker/Dockerfile-headless
+++ b/docker/Dockerfile-headless
@@ -33,11 +33,13 @@ RUN curl -sLo ~/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-py39
 
 # install
 RUN conda install python=3.7 -y
-RUN pip install setuptools --upgrade && pip install --upgrade pip
-RUN conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
+RUN pip install --upgrade pip
+# RUN conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
 
-# # needed for pandas for some reason
+# Install deepethogram with dev dependencies
 ADD . /app/deepethogram
 WORKDIR /app/deepethogram
+# Use Python 3.7 compatible pyproject.toml
+RUN cp pyproject_py37.toml pyproject.toml
 ENV DEG_VERSION='headless'
-RUN pip install -e .
+RUN pip install -e ".[dev]"
diff --git a/docker/build_and_test.sh b/docker/build_and_test.sh
new file mode 100755
index 0000000..71fc214
--- /dev/null
+++ b/docker/build_and_test.sh
@@ -0,0 +1,134 @@
+#!/bin/bash
+
+set -e  # Exit on any error
+
+# Colors for output
+GREEN='\033[0;32m'
+RED='\033[0;31m'
+NC='\033[0m' # No Color
+BLUE='\033[0;34m'
+YELLOW='\033[1;33m'
+
+# Function to print section headers
+print_header() {
+    echo -e "\n${BLUE}=== $1 ===${NC}\n"
+}
+
+# Function to echo command before running
+echo_run() {
+    echo -e "${YELLOW}Running: $@${NC}"
+    "$@"
+}
+
+# Function to build an image
+build_image() {
+    local type=$1
+    print_header "Building $type image"
+    echo_run docker build -t deepethogram:$type -f docker/Dockerfile-$type .
+}
+
+# Function to verify GPU in container
+verify_gpu() {
+    local gpu_flag=$1
+    local type=$2
+    echo "Verifying GPU access in container..."
+    echo -e "${YELLOW}Running: docker run $gpu_flag --rm deepethogram:$type nvidia-smi${NC}"
+    if ! docker run $gpu_flag --rm deepethogram:$type nvidia-smi; then
+        echo -e "${RED}Failed to access GPU in container${NC}"
+        return 1
+    fi
+    echo -e "${YELLOW}Running: docker run $gpu_flag --rm deepethogram:$type python -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"${NC}"
+    if ! docker run $gpu_flag --rm deepethogram:$type python -c "import torch; print('CUDA available:', torch.cuda.is_available())" | grep -q "CUDA available: True"; then
+        echo -e "${RED}Failed to access GPU through PyTorch${NC}"
+        return 1
+    fi
+    return 0
+}
+
+# Function to run tests in container
+test_container() {
+    local type=$1
+    local gpu_flag=$2
+    local has_gpu=$3
+
+    print_header "Testing $type container"
+
+    # Test basic import
+    echo "Testing Python import..."
+    echo -e "${YELLOW}Running: docker run $gpu_flag -it deepethogram:$type python -c \"import deepethogram\"${NC}"
+    docker run $gpu_flag -it deepethogram:$type python -c "import deepethogram" && \
+        echo -e "${GREEN}✓ Import test passed${NC}" || \
+        (echo -e "${RED}✗ Import test failed${NC}" && exit 1)
+
+    # For containers that should support tests
+    if [ "$type" = "full" ] || [ "$type" = "headless" ]; then
+        echo "Running CPU tests..."
+        echo -e "${YELLOW}Running: docker run $gpu_flag -it deepethogram:$type pytest -v -m \"not gpu\" tests/${NC}"
+        docker run $gpu_flag -it deepethogram:$type pytest -v -m "not gpu" tests/ && \
+            echo -e "${GREEN}✓ CPU tests passed${NC}" || \
+            (echo -e "${RED}✗ CPU tests failed${NC}" && exit 1)
+
+        # Run GPU tests if GPU is available
+        if [ "$has_gpu" = true ] && [ "$type" != "gui" ]; then
+            echo "Running GPU tests..."
+            # First verify CUDA is accessible
+            echo -e "${YELLOW}Running: docker run $gpu_flag -it deepethogram:$type python -c \"import torch; assert torch.cuda.is_available(), 'CUDA not available'; print('CUDA is available')\"${NC}"
+            docker run $gpu_flag -it deepethogram:$type python -c "import torch; assert torch.cuda.is_available(), 'CUDA not available'; print('CUDA is available')"
+            # Run the actual GPU tests
+            echo -e "${YELLOW}Running: docker run $gpu_flag -it deepethogram:$type bash -c \"export CUDA_VISIBLE_DEVICES=0 && pytest -v -m gpu tests/\"${NC}"
+            docker run $gpu_flag -it deepethogram:$type \
+                bash -c "export CUDA_VISIBLE_DEVICES=0 && pytest -v -m gpu tests/" && \
+                echo -e "${GREEN}✓ GPU tests passed${NC}" || \
+                (echo -e "${RED}✗ GPU tests failed${NC}" && exit 1)
+        fi
+    fi
+
+    # For containers that should support GUI
+    if [ "$type" = "full" ] || [ "$type" = "gui" ]; then
+        echo "Testing GUI import..."
+        echo -e "${YELLOW}Running: docker run $gpu_flag -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:rw -it deepethogram:$type python -c \"from deepethogram.gui import main\"${NC}"
+        docker run $gpu_flag -e DISPLAY=$DISPLAY \
+            -v /tmp/.X11-unix:/tmp/.X11-unix:rw \
+            -it deepethogram:$type python -c "from deepethogram.gui import main" && \
+            echo -e "${GREEN}✓ GUI import test passed${NC}" || \
+            (echo -e "${RED}✗ GUI import test failed${NC}" && exit 1)
+    fi
+}
+
+# Main execution
+main() {
+    # Ensure we're in the project root
+    if [[ ! -f "pyproject.toml" ]]; then
+        echo -e "${RED}Error: Must run from project root directory (where pyproject.toml is located)${NC}"
+        exit 1
+    fi
+
+    # Check if GPU is available by testing nvidia-smi
+    local has_gpu=false
+    if command -v nvidia-smi &> /dev/null && nvidia-smi &> /dev/null; then
+        GPU_FLAG="--gpus all"
+        has_gpu=true
+        echo -e "${GREEN}NVIDIA GPU detected, will use GPUs and run GPU tests${NC}"
+    else
+        GPU_FLAG=""
+        echo -e "${RED}No NVIDIA GPU detected, running without GPU${NC}"
+    fi
+
+    # Build and test each image type
+    for type in "headless" "gui" "full"; do
+        build_image $type
+        # Verify GPU access after building if we have a GPU
+        if [ "$has_gpu" = true ] && [ "$type" != "gui" ]; then
+            if ! verify_gpu "$GPU_FLAG" "$type"; then
+                echo -e "${RED}GPU detected on host but not accessible in container. Please check nvidia-docker installation.${NC}"
+                exit 1
+            fi
+        fi
+        test_container $type "$GPU_FLAG" $has_gpu
+    done
+
+    print_header "All builds and tests completed successfully!"
+}
+
+# Execute main function
+main
diff --git a/docs/cleanup_plan.md b/docs/cleanup_plan.md
new file mode 100644
index 0000000..f867848
--- /dev/null
+++ b/docs/cleanup_plan.md
@@ -0,0 +1,375 @@
+# DeepEthogram Repository Cleanup Plan
+
+## Executive Summary
+
+This document outlines a comprehensive cleanup plan for the DeepEthogram repository to modernize the codebase, improve maintainability, and enhance user experience. The cleanup is organized into phases to ensure systematic improvement without breaking existing functionality.
+
+**Last Updated**: January 2025  
+**Current Branch**: cleanup (partially implemented)
+
+## Progress Status
+
+### ✅ Already Completed on Cleanup Branch
+- Migrated from setup.py to pyproject.toml
+- Consolidated dependencies (removed requirements.txt)
+- Simplified installation process
+- Added Docker build and test script
+- Updated CI/CD workflows
+- Added UV package manager support (beta)
+
+## Phase 1: PyTorch Lightning & Installation Fixes (1 week) 🚨
+
+### 1.1 PyTorch Lightning Compatibility (HIGHEST PRIORITY)
+**Status**: ❌ Not Started - **Fixes Issues #163, #145, #158**
+**Note**: Stay on Python 3.7 to avoid PySide complications
+- [ ] Create compatibility layer for Lightning 1.6.5 → 2.x
+- [ ] Option A: Pin to intermediate version (1.9.x) that works with Python 3.7
+- [ ] Option B: Add compatibility shims:
+  - [ ] Detect Lightning version and use appropriate API calls
+  - [ ] Wrap trainer instantiation with version checks
+  - [ ] Fix `reload_dataloaders_every_epoch` parameter issue
+  - [ ] Fix `progress_bar_refresh_rate` parameter issue  
+  - [ ] Fix `gpus` vs `accelerator` parameter
+  - [ ] Fix FPSCallback `dataloader_idx` parameter
+- [ ] Test all training pipelines
+- [ ] Document Lightning version requirements
+
+### 1.2 NumPy Compatibility Fix
+**Status**: ❌ Not Started - **Fixes Issue #155**
+- [ ] Replace all `np.float` with `float` or `np.float64`
+- [ ] Replace all `np.int` with `int` or `np.int64`
+- [ ] Add numpy version constraint compatible with Python 3.7
+- [ ] Test with numpy 1.21.x (last to support Python 3.7 well)
+
+### 1.3 Hydra/OmegaConf Conflict Resolution
+**Status**: ❌ Not Started - **Fixes Issue #144**
+- [ ] Fix hydra detection in `__init__.py`
+- [ ] Ensure omegaconf version compatibility
+- [ ] Add clear error message if hydra-core is installed
+- [ ] Test installation from clean environment
+
+### 1.4 Installation & Dependency Fixes (Python 3.7 compatible)
+**Status**: ⚠️ Build system ready, dependencies not updated
+- [ ] Fix scikit-learn 1.0.2 installation for Python 3.7
+- [ ] Update dependencies that work with Python 3.7:
+  - [ ] pandas to highest version supporting 3.7 (1.3.5)
+  - [ ] scikit-learn to 1.0.2 (with proper build deps)
+  - [ ] scipy to highest 3.7-compatible version
+- [ ] Create requirements-colab.txt for Colab-specific deps
+- [ ] Test installation on fresh systems
+
+### 1.5 Critical GUI Fixes (without PySide upgrade)
+- [ ] Fix dropdown menu issue (#166) - pretrained weights not selectable
+- [ ] Add debugging for Qt platform issues
+- [ ] Create platform-specific installation guides
+- [ ] Add GUI error recovery mechanisms
+
+## Phase 2: Stabilization and Testing (1-2 weeks)
+
+### 2.1 Test Suite Fixes
+**Status**: ⚠️ Docker test script added, but tests may fail
+- [ ] Fix all tests broken by dependency updates
+- [ ] Add compatibility shims for PyTorch Lightning changes
+- [ ] Mock GPU tests for CI/CD without GPU
+- [ ] Ensure Docker tests pass for all images
+- [ ] Add regression tests for fixed issues
+
+### 2.2 Documentation Updates
+**Status**: ⚠️ Some docs added, critical gaps remain
+- [ ] Complete CLI documentation (#169, #170)
+- [ ] Fill in empty `model_performance.md`
+- [ ] Create troubleshooting guide for common issues:
+  - [ ] Installation failures by OS
+  - [ ] GPU detection problems
+  - [ ] Qt/GUI issues
+  - [ ] Dependency conflicts
+- [ ] Update README with new Python version requirements
+
+### 2.3 Installation Verification
+- [ ] Test installation on fresh systems:
+  - [ ] Ubuntu 20.04, 22.04
+  - [ ] Windows 10, 11
+  - [ ] macOS 12, 13, 14
+- [ ] Verify Colab notebook works (#173)
+- [ ] Test conda environment creation
+- [ ] Verify UV installation method
+
+## Phase 3: Python Version Upgrade (2-3 weeks)
+
+### 3.1 Python 3.8+ Migration Planning
+**Status**: ❌ Deferred until core issues fixed
+**Dependencies**: Requires PySide2 → PySide6 migration
+- [ ] Create detailed migration plan for PySide2 → PySide6
+- [ ] Identify all Qt-dependent code sections
+- [ ] Plan phased migration approach
+- [ ] Test PySide6 compatibility on all platforms
+
+### 3.2 Python Version Update
+**After PySide6 migration is complete**
+- [ ] Update Python constraint to `>=3.8,<3.12`
+- [ ] Update all Docker base images
+- [ ] Update conda environment
+- [ ] Test on Python 3.8, 3.9, 3.10, 3.11
+
+### 3.3 Modern Dependency Updates
+**Only after Python 3.8+ is working**
+- [ ] Update to latest compatible versions:
+  - [ ] pytorch_lightning to 2.x
+  - [ ] pandas to 2.x
+  - [ ] numpy to 1.24+
+  - [ ] scikit-learn to 1.3+
+  - [ ] scipy to 1.11+
+
+## Phase 4: Long-term Improvements (3-4 weeks)
+
+### 4.1 Complete PySide6 Migration
+**Status**: ❌ Planning needed
+- [ ] Create migration plan from PySide2 to PySide6
+- [ ] Update all Qt imports and API calls
+- [ ] Test on all platforms
+- [ ] Update Docker images with new Qt
+- [ ] Document any breaking changes
+
+### 4.2 Feature Requests Implementation
+- [ ] Batch video selection for inference (#143)
+- [ ] Resume training from checkpoint (#149)
+- [ ] Better error messages for missing weights
+- [ ] Improved model selection UI
+- [ ] Add progress bars for long operations
+
+### 4.3 Code Quality and Refactoring
+- [ ] Address remaining TODO items
+- [ ] Add type hints throughout codebase
+- [ ] Improve error handling
+- [ ] Refactor configuration system (#1168)
+- [ ] Remove redundant parameters (#94)
+
+## Phase 5: Architecture Refactoring (3-4 weeks)
+
+### 5.1 Code Structure Improvements
+- [ ] Separate GUI logic from core functionality
+- [ ] Create clear API boundaries
+- [ ] Implement dependency injection where appropriate
+- [ ] Refactor configuration system for clarity
+
+### 5.2 Model Architecture Updates
+- [ ] Update model implementations to use latest PyTorch features
+- [ ] Implement model registry pattern
+- [ ] Add support for custom model architectures
+- [ ] Create model zoo with pretrained weights
+
+### 5.3 Plugin System
+- [ ] Design plugin architecture for extensions
+- [ ] Create plugin API
+- [ ] Implement example plugins
+- [ ] Document plugin development
+
+## Phase 6: Advanced Features (4-6 weeks)
+
+### 6.1 Workflow Automation
+- [ ] Create CLI for batch processing
+- [ ] Add experiment tracking (MLflow/W&B integration)
+- [ ] Implement automatic hyperparameter tuning
+- [ ] Add continuous learning pipeline
+
+### 6.2 Cloud and Deployment
+- [ ] Create Docker images for different use cases
+- [ ] Add Kubernetes deployment configurations
+- [ ] Implement REST API for remote inference
+- [ ] Create cloud-friendly storage backends
+
+### 6.3 Extended Functionality
+- [ ] Add multi-animal tracking support
+- [ ] Implement real-time inference mode
+- [ ] Add support for additional video formats
+- [ ] Create behavior analysis tools
+
+## Critical Path and Priority Order
+
+### 🔴 MUST DO FIRST (Stay on Python 3.7):
+1. **PyTorch Lightning compatibility** - Add shims/version detection
+2. **NumPy deprecations** - Fix np.float/np.int usage
+3. **Installation fixes** - Hydra conflicts, scikit-learn builds
+4. **GUI dropdown fix** - Unblocks workflow
+
+### 🟡 THEN FIX (Still Python 3.7):
+1. Colab notebook compatibility
+2. Qt platform fixes (workarounds)
+3. Documentation completion
+4. Testing improvements
+
+### 🟢 FINALLY UPGRADE (Requires planning):
+1. PySide2 → PySide6 migration
+2. Python 3.8+ support
+3. Modern dependency versions
+4. Performance optimizations
+
+## Implementation Guidelines
+
+### Quick Wins First
+Start with changes that:
+- Have minimal risk
+- Fix the most user-reported issues
+- Can be tested easily
+- Don't require major refactoring
+
+### Version Control Strategy
+1. **Current branch (cleanup)**: Already has build improvements
+2. Create sub-branches for each critical fix
+3. Test each fix independently
+4. Merge incrementally with thorough testing
+5. Tag pre-release versions for testing
+
+### Testing Requirements
+For EACH change:
+1. Run existing test suite
+2. Test on at least 2 OS platforms
+3. Verify GUI still works
+4. Test training pipeline end-to-end
+5. Check Colab compatibility
+
+### Breaking Changes Communication
+1. Create migration guide for Lightning 2.x
+2. Document Python version requirements clearly
+3. Provide compatibility shims where possible
+4. Give users warning before major releases
+
+## Success Metrics
+
+### Immediate Success Criteria (Phase 1)
+- [ ] Installation works on Python 3.8+ 
+- [ ] Colab notebook functional
+- [ ] Training runs without Lightning errors
+- [ ] GUI dropdowns work
+- [ ] 90% of open issues addressed or have workarounds
+
+### Overall Project Health
+- [ ] Test coverage > 80%
+- [ ] CI/CD passes on all platforms
+- [ ] Documentation complete for all features
+- [ ] <5 critical bugs reported per month
+- [ ] Installation success rate > 95%
+
+## Risk Mitigation
+
+### Potential Risks
+1. **Breaking Changes**: Maintain compatibility layer
+2. **Performance Regression**: Benchmark before/after
+3. **User Disruption**: Provide migration guides
+4. **Dependency Conflicts**: Test thoroughly
+5. **Data Loss**: Implement backup mechanisms
+
+### Mitigation Strategies
+1. Comprehensive testing at each phase
+2. Gradual rollout with beta testing
+3. Maintain stable branch during development
+4. Document all changes thoroughly
+5. Provide rollback procedures
+
+## Revised Timeline Based on Current Status
+
+### Already Completed (on cleanup branch)
+- ✅ Build system modernization (setup.py → pyproject.toml)
+- ✅ Docker improvements
+- ✅ Installation simplification
+
+### Immediate Actions (Week 1) - Stay on Python 3.7
+- 🔴 Fix PyTorch Lightning compatibility with shims
+- 🔴 Fix NumPy deprecations
+- 🔴 Fix installation issues (Hydra, scikit-learn)
+- 🔴 Fix GUI dropdown bug
+
+### Short Term (Weeks 2-3) - Still Python 3.7
+- 🟡 Stabilize all installations
+- 🟡 Fix Colab notebook
+- 🟡 Complete documentation
+- 🟡 Platform-specific fixes
+
+### Medium Term (Weeks 4-6) - Python upgrade
+- 🟢 PySide2 → PySide6 migration
+- 🟢 Python 3.8+ upgrade
+- 🟢 Modern dependency updates
+
+### Long Term (Weeks 7-10)
+- 🔵 Performance optimizations
+- 🔵 Feature additions
+- 🔵 Architecture improvements
+
+### Total: 2 months for critical fixes, 4 months for full modernization
+
+## Immediate Next Steps
+
+1. **Test current cleanup branch thoroughly**
+   ```bash
+   ./docker/build_and_test.sh  # Already available!
+   ```
+
+2. **Create Lightning compatibility branch (Python 3.7)**
+   ```bash
+   git checkout -b lightning-compat-py37
+   # Add version detection in base.py
+   # Create compatibility shims
+   # Test with Lightning 1.6.5 and 1.9.x
+   ```
+
+3. **Fix NumPy and installation issues**
+   ```bash
+   git checkout -b fix-numpy-install
+   # Replace np.float/np.int
+   # Fix Hydra detection
+   # Test fresh installations
+   ```
+
+4. **Fix GUI dropdown bug**
+   ```bash
+   git checkout -b fix-gui-dropdown
+   # Debug pretrained weight selection
+   # Test on multiple platforms
+   ```
+
+5. **Only after above are stable:**
+   ```bash
+   git checkout -b pyside6-python38
+   # Plan PySide migration first
+   # Then upgrade Python version
+   ```
+
+## GitHub Issues Resolution Map
+
+| Issue | Fix Location | Priority | Phase | Python Upgrade Required |
+|-------|-------------|----------|-------|------------------------|
+| #163 (Flow generator) | base.py - Lightning shims | 🔴 Critical | 1 | No |
+| #155 (NumPy) | Throughout - np.float | 🔴 Critical | 1 | No |
+| #144 (Hydra) | __init__.py | 🔴 Critical | 1 | No |
+| #166 (Dropdowns) | gui/main.py | 🔴 Critical | 1 | No |
+| #173 (Colab install) | scikit-learn deps | 🟡 High | 2 | Partial |
+| #171 (macOS GUI) | Qt workarounds | 🟡 High | 2 | No |
+| #164 (Windows Qt) | Platform guide | 🟡 High | 2 | No |
+| #172 (Training) | Documentation | 🟢 Medium | 2 | No |
+
+## Key Strategy Change
+
+### Why Stay on Python 3.7 Initially?
+- **PySide2 → PySide6 is a MAJOR migration** requiring:
+  - Rewriting all Qt imports and many API calls
+  - Extensive GUI testing on all platforms  
+  - Potentially breaking changes for users
+- **Most critical issues can be fixed WITHOUT Python upgrade**:
+  - PyTorch Lightning: Use compatibility shims
+  - NumPy: Simple find/replace of deprecated calls
+  - Installation: Fix dependencies within Python 3.7 constraints
+
+### Phased Approach Benefits
+1. **Phase 1**: Fix critical blockers while maintaining stability
+2. **Phase 2**: Stabilize and document workarounds
+3. **Phase 3**: Plan and execute PySide6 + Python upgrade together
+4. **Phase 4**: Modernize with latest dependencies
+
+This approach gets users unblocked FAST while planning the bigger migration carefully.
+
+## Notes
+
+- **Good News**: Build system already modernized on cleanup branch
+- **New Priority**: Fix issues WITHOUT Python upgrade first
+- **Testing**: Use new Docker test script for validation
+- **Communication**: Be clear about phased approach to users
\ No newline at end of file
diff --git a/docs/development_setup.md b/docs/development_setup.md
new file mode 100644
index 0000000..f6deac8
--- /dev/null
+++ b/docs/development_setup.md
@@ -0,0 +1,163 @@
+# DeepEthogram Development Setup and Test Results
+
+## Setup Date: January 2025
+
+## System Information
+- **OS**: Linux 5.19.5-051905-generic
+- **GPUs**: 2x NVIDIA GeForce RTX 3090 (24GB VRAM each)
+- **Python**: System has 3.10.12, project requires 3.7
+
+## Development Environment Setup
+
+### Using UV Package Manager
+Successfully set up with UV (v0.8.8) but with a critical modification:
+- **Changed Python requirement** from `>=3.7,<3.8` to `>=3.8,<3.9` temporarily
+- This allows UV to manage the environment (UV doesn't support Python 3.7)
+- Created `.venv` with Python 3.8.20
+
+### Installation Command
+```bash
+# After modifying pyproject.toml to allow Python 3.8
+uv sync
+```
+
+### Created Files
+- `.venv/` - Virtual environment with Python 3.8.20
+- `uv.lock` - Locked dependencies for reproducible builds
+
+## Test Results Summary
+
+### Non-GUI Tests: ✅ PASSING (12/12)
+```bash
+source .venv/bin/activate && pytest tests/ -v --ignore=tests/test_gui.py
+```
+
+All core functionality tests pass:
+- `test_data.py::test_loss_weight` ✅
+- `test_flow_generator.py::test_metrics` ✅
+- `test_models.py::test_get_cnn` ✅
+- `test_projects.py` (8 tests) ✅
+- `test_z_score.py::test_single_video` ✅
+
+### GUI Tests: ❌ FAILING (0/1)
+```bash
+tests/test_gui.py::test_setup FAILED
+```
+**Error**: `TypeError: 'Shiboken.ObjectType' object is not iterable`
+- Location: `deepethogram/gui/custom_widgets.py:176`
+- Cause: PySide2 5.13.2 incompatibility with Python 3.8
+- **This is why Python was pinned to 3.7**
+
+### GPU Tests: ⚠️ TIMEOUT
+- Integration tests with GPU (`test_integration.py`) start but timeout after 2 minutes
+- `test_flow` passes but other tests hang
+
+## Key Issues Identified
+
+### 1. Python Version Constraint
+- **Root Cause**: PySide2 5.13.2 requires Python 3.7
+- **Impact**: Cannot use modern Python (3.8+) without migrating to PySide6
+- **Current Workaround**: Using Python 3.8 for non-GUI development
+
+### 2. Test Warnings
+- PyTorch FutureWarning about `weights_only=False` in torch.load
+- Kornia deprecation warning about `torch.cuda.amp.custom_fwd`
+- Both are upstream dependency issues, not critical
+
+### 3. Development vs Production
+- Development can proceed with Python 3.8 for core functionality
+- GUI development still requires Python 3.7 or PySide migration
+- Docker tests can validate Python 3.7 compatibility
+
+## Recommendations
+
+### Immediate Actions
+1. **For Core Development**: Continue with Python 3.8 setup
+2. **For GUI Testing**: Use Docker with Python 3.7
+3. **For CI/CD**: Keep dual testing (UV for core, Docker for full)
+
+### Medium-term Solutions
+1. **Create compatibility shims** for PyTorch Lightning
+2. **Fix NumPy deprecations** (np.float, np.int)
+3. **Investigate PySide2 fixes** for Python 3.8 or plan PySide6 migration
+
+### Testing Strategy
+```bash
+# Core tests (Python 3.8 with UV)
+source .venv/bin/activate
+pytest tests/ --ignore=tests/test_gui.py
+
+# Full tests including GUI (Python 3.7 with Docker)
+./docker/build_and_test.sh
+```
+
+## Docker Setup and Testing
+
+### Docker Images Built
+Three Docker images have been successfully built and tested with Python 3.7:
+
+1. **deepethogram:headless** - GPU support, no GUI (25.4GB)
+   - ✅ nvidia-smi working
+   - ✅ CUDA available in PyTorch
+   - ✅ All tests pass
+
+2. **deepethogram:gui** - CPU-only, GUI support (13.5GB)
+   - ✅ GUI imports and runs successfully
+   - ✅ Uses pip-installed PyTorch 1.11.0+cpu to avoid conda/Python 3.7 compatibility issues
+   - ✅ GUI window displays correctly with X11 forwarding
+
+3. **deepethogram:full** - GPU + GUI support (built from Dockerfile-full)
+   - ✅ nvidia-smi working
+   - ✅ CUDA available in PyTorch (1.13.1+cu117)
+   - ✅ GUI imports and runs successfully
+   - ✅ Detects both RTX 3090 GPUs
+
+### Key Docker Findings
+
+#### Python 3.7 + PyTorch Compatibility Issue
+- **Problem**: Conda-installed PyTorch (1.13.1, 1.12.1, 1.11.0) with CPU-only builds fail on Python 3.7
+- **Error**: `undefined symbol: iJIT_NotifyEvent` in libtorch_cpu.so
+- **Solution**: Install PyTorch via pip instead of conda for CPU-only builds
+- **Applied to**: Dockerfile-gui now uses:
+  ```dockerfile
+  RUN pip install torch==1.11.0+cpu torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+  ```
+
+#### GPU Support Verification
+Both headless and full containers successfully:
+- Access both RTX 3090 GPUs
+- Show correct CUDA version (11.5.2 in container, 12.1 driver)
+- Report CUDA available in PyTorch
+- Can run GPU-accelerated computations
+
+#### GUI Testing with X11
+To run GUI from Docker:
+```bash
+# Allow Docker X11 access
+xhost +local:docker
+
+# Run GUI with display forwarding
+docker run --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:rw --net=host deepethogram:gui deepethogram
+
+# For GPU-enabled GUI
+docker run --rm --gpus all -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix:rw --net=host deepethogram:full deepethogram
+```
+
+### Docker Test Commands
+```bash
+# Build and test all images
+./docker/build_and_test.sh
+
+# Test GPU access
+docker run --rm --gpus all deepethogram:headless nvidia-smi
+docker run --rm --gpus all deepethogram:full python -c "import torch; print(torch.cuda.is_available())"
+
+# Test GUI
+docker run --rm deepethogram:gui python -c "from deepethogram.gui import main; print('GUI works!')"
+```
+
+## Next Steps
+1. ~~Run Docker tests to validate Python 3.7 compatibility~~ ✅ Complete
+2. ~~Investigate PySide2/Python 3.8 compatibility fixes~~ ✅ Root cause identified
+3. Begin implementing PyTorch Lightning compatibility shims
+4. Consider migrating from PySide2 to PySide6 for Python 3.8+ support
\ No newline at end of file
diff --git a/docs/installation.md b/docs/installation.md
index 313f148..1c57f50 100644
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -1,20 +1,39 @@
 # Installation
 
-## Brief version
+## Quick Install with UV (Recommended for v0.3.0+)
+
+We now recommend using [UV](https://docs.astral.sh/uv/) for fast, reliable installation:
+
+1. **Install UV**:
+   ```bash
+   curl -LsSf https://astral.sh/uv/install.sh | sh
+   # or see the uv website for Windows instructions
+   ```
+
+2. **Create environment and install**:
+   ```bash
+   uv venv --python 3.8
+   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+   uv pip install deepethogram
+   ```
+
+**Note**: DeepEthogram v0.3.0+ requires Python 3.8 and uses PySide6 (upgraded from PySide2).
+
+## Traditional Installation, NOT RECOMMENDED!
+
+### Brief version
 * Install Anaconda
-* Create a new anaconda environment: `conda create --name deg python=3.7`
+* Create a new anaconda environment: `conda create --name deg python=3.8`
 * Activate your environment: `conda activate deg`
-* Install PySide2: `conda install -c conda-forge pyside2==5.13.2`
 * Install PyTorch: [Use this link for official instructions.](https://pytorch.org/)
-* `pip install deepethogram`.
+* `pip install deepethogram`
 
-## Installing from source
+### Installing from source
 * `git clone https://github.com/jbohnslav/deepethogram.git`
 * `cd deepethogram`
-* `conda env create -f environment.yml`
-    * Be prepared to wait a long time!! On mechanical hard drives, this may take 5-10 minutes (or more). Interrupting here will cause installation to fail.
+* `conda create --name deg python=3.8`
 * `conda activate deg`
-* `python setup.py develop`
+* `pip install -e .`
 
 ### Installing Anaconda
 For instructions on installing anaconda,
@@ -26,31 +45,24 @@ you can have both installed on your machine without interference.
 * Install git for your operating system (a good idea anyway!) [Downloads page here](https://git-scm.com/download)
 * Open up the command line, such as terminal on mac or cmd.exe. **VERY IMPORTANT: On Windows, make sure you run the command prompt as an administrator! To do this, right click the shortcut to the command prompt, click `run as administrator`, then say yes to whatever pops up.**
 
-## Installing from pip
-First install the latest version of PyTorch for your system. [Use this link for official instructions.](https://pytorch.org/)
-It should be as simple as `conda install pytorch torchvision cudatoolkit=10.2 -c pytorch`.
-
-Note: if you have an RTX3000 series graphics card, such as a 3060 or 3090, please use `cudatoolkit=11.1` or higher.
-
-After installing PyTorch, simply use `pip install deepethogram`.
-
 ## Install FFMPEG
 We use FFMPEG for reading and writing `.mp4` files (with libx264 encoding). Please use [this link](https://www.ffmpeg.org/)
 to install on your system.
 
 ## Startup
-* `conda activate deg`. This activates the environment.
-* type `python -m deepethogram`, in the command line to open the GUI.
-
-## Upgrading to Beta
-Please see [the beta docs for instructions](beta.md)
+* `source.venv/bin/python` or (old version) `conda activate deg`. This activates the environment.
+* type `deepethogram` in the command line to open the GUI.
 
-## Common installation problems
+## Common installation problems (with old, conda installers)
 * You might have dependency issues with other packages you've installed. Please make a new anaconda or miniconda
 environment with `conda create --name deg python=3.8` before installation.
-* `module not found: PySide2`. Some versions of PySide2 install poorly from pip. use `pip uninstall pyside2`, then
+* `module not found: PySide2` or `module not found: PySide6`. 
+  * For v0.3.0+, we use PySide6. Try: `pip install --force-reinstall PySide6`
+  * For older versions with PySide2: Some versions of PySide2 install poorly from pip. use `pip uninstall pyside2`, then
 `conda install -c conda-forge pyside2`
-* When opening the GUI, you might get `Segmentation fault (core dumped)`. In this case; please `pip uninstall pyside2`,
+* When opening the GUI, you might get `Segmentation fault (core dumped)`. 
+  * For PySide6 (v0.3.0+): `pip install --force-reinstall PySide6`
+  * For PySide2 (older versions): In this case; please `pip uninstall pyside2`,
 `conda uninstall pyside2`. `pip install pyside2`
 * `ImportError: C:\Users\jbohn\.conda\envs\deg2\lib\site-packages\shiboken2\libshiboken does not exist`
   * something went wrong with your PySide2 installation, likely on Windows.
@@ -61,4 +73,4 @@ environment with `conda create --name deg python=3.8` before installation.
 * `_init_pyside_extension is not defined`
   * This is an issue where Shiboken and PySide2 are not playing nicely together. Please `pip uninstall pyside2` and `conda remove pyside2`. Don't manually install these packages; instead, let DeepEthogram install it for you via pip. Therefore, `pip uninstall deepethogram` and `pip install deepethogram`.
 *  `qt.qpa.plugin: Could not load the Qt platform plugin "xcb" in ".../python3.8/site-packages/cv2/qt/plugins"  even though it was found. This application failed to start because no Qt platform plugin could be initialized. Reinstalling the application may fix this problem.`
-   * This is an issue with a recent version of `opencv-python` not working well with Qt. Please do `pip install --force-reinstall opencv-python-headless==4.1.2.30`
+   * This is an issue with a recent version of `opencv-python` not working well with Qt. Please do `pip install --force-reinstall opencv-python-headless==4.1.2.30`
\ No newline at end of file
diff --git a/environment.yml b/environment.yml
index bb3dccc..2ba47c7 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,9 +4,10 @@ channels:
   - conda-forge
   - defaults
 dependencies:
+  - python=3.7
+  - pytorch
+  - torchvision
   - pip
-  - conda-forge::pyside2=5.13.2
-  - python>3.7, <3.9
-  - pytorch::pytorch
   - pip:
-    - -r requirements.txt
+    - -e .
+  - conda-forge::pyside2=5.13.2
diff --git a/pyproject.toml b/pyproject.toml
index c099f91..a70a9a3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,57 @@
+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "deepethogram"
+version = "0.3.0"
+description = "Temporal action detection for biology"
+readme = "README.md"
+authors = [
+    {name = "Jim Bohnslav", email = "jbohnslav@gmail.com"},
+]
+requires-python = ">=3.8,<3.9"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "chardet<4.0",
+    "h5py",
+    "kornia>=0.5",
+    "matplotlib",
+    "numpy",
+    "omegaconf>=2",
+    "opencv-python-headless",
+    "opencv-transforms",
+    "pandas<1.4",
+    "PySide6>=6.6.0",
+    "scikit-learn<1.1",
+    "scipy<1.8",
+    "tqdm",
+    "vidio",
+    "pytorch_lightning==1.6.5",
+]
+
+[dependency-groups]
+dev = [
+    "ruff>=0.1.0",
+    "pre-commit>=2.20.0,<3.0.0",
+    "pytest",
+    "pytest-cov",
+    "gdown",
+    "ty>=0.0.1a17",
+]
+
+[project.scripts]
+deepethogram = "deepethogram.gui.main:entry"
+
+[tool.setuptools]
+packages = ["deepethogram"]
+
 [tool.ruff]
 # Python version compatibility
-target-version = "py37"
+target-version = "py38"
 
 # Same as Black.
 line-length = 120
@@ -33,7 +84,6 @@ exclude = [
 ]
 
 [tool.ruff.lint]
-
 # Allow autofix for all enabled rules (when `--fix`) is provided.
 fixable = ["ALL"]
 unfixable = []
diff --git a/pyproject_py37.toml b/pyproject_py37.toml
new file mode 100644
index 0000000..cefd73a
--- /dev/null
+++ b/pyproject_py37.toml
@@ -0,0 +1,88 @@
+[build-system]
+requires = ["setuptools>=42", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "deepethogram"
+version = "0.2.0"
+description = "Temporal action detection for biology"
+readme = "README.md"
+authors = [
+    {name = "Jim Bohnslav", email = "jbohnslav@gmail.com"},
+]
+requires-python = ">=3.7,<3.8"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "chardet<4.0",
+    "h5py",
+    "kornia>=0.5",
+    "matplotlib",
+    "numpy",
+    "omegaconf>=2",
+    "opencv-python-headless",
+    "opencv-transforms",
+    "pandas<1.4",
+    "PySide2==5.13.2",
+    "scikit-learn<1.1",
+    "scipy<1.8",
+    "tqdm",
+    "vidio",
+    "pytorch_lightning==1.6.5",
+]
+
+[project.optional-dependencies]
+dev = [
+    "ruff>=0.1.0",
+    "pre-commit>=2.20.0,<3.0.0",
+    "pytest",
+    "pytest-cov",
+    "gdown",
+]
+
+[project.scripts]
+deepethogram = "deepethogram.gui.main:entry"
+
+[tool.setuptools]
+packages = ["deepethogram"]
+
+[tool.ruff]
+# Python version compatibility
+target-version = "py37"
+
+# Same as Black.
+line-length = 120
+
+# Exclude a variety of commonly ignored directories.
+exclude = [
+    ".bzr",
+    ".direnv",
+    ".eggs",
+    ".git",
+    ".git-rewrite",
+    ".hg",
+    ".mypy_cache",
+    ".nox",
+    ".pants.d",
+    ".pytype",
+    ".ruff_cache",
+    ".svn",
+    ".tox",
+    ".venv",
+    "__pypackages__",
+    "_build",
+    "buck-out",
+    "build",
+    "dist",
+    "node_modules",
+    "venv",
+    "tests/",
+    "docs/"
+]
+
+[tool.ruff.lint]
+# Allow autofix for all enabled rules (when `--fix`) is provided.
+fixable = ["ALL"]
+unfixable = []
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 9626e8d..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,20 +0,0 @@
-chardet<4.0
-h5py
-kornia>=0.5
-matplotlib
-numpy
-omegaconf>=2
-opencv-python-headless
-opencv-transforms
-pandas<1.4
-PySide2==5.13.2
-pytest
-scikit-learn<1.1
-scipy<1.8
-tqdm
-vidio
-pytorch_lightning==1.6.5
-ruff>=0.1.0
-pre-commit>=2.20.0,<3.0.0
-setuptools
-gdown
diff --git a/reset_venv.sh b/reset_venv.sh
index bfd5d8e..8ffab47 100755
--- a/reset_venv.sh
+++ b/reset_venv.sh
@@ -14,17 +14,9 @@ uv venv --python 3.7
 echo "Activating virtual environment..."
 source .venv/bin/activate
 
-# Install requirements first
-echo "Installing requirements..."
-uv pip install -r requirements.txt
-
-# Install pytest
-echo "Installing pytest..."
-uv pip install pytest pytest-cov
-
-# Install package in editable mode
-echo "Installing package in editable mode..."
-uv pip install -e .
+# Install package in editable mode with dev dependencies
+echo "Installing package and dependencies..."
+uv pip install -e ".[dev]"
 
 # Setup test data
 echo "Setting up test data..."
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 971ff08..0000000
--- a/setup.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import setuptools
-
-with open("README.md", "r") as f:
-    long_description = f.read()
-
-
-def get_requirements():
-    with open("requirements.txt") as f:
-        return f.read().splitlines()
-
-
-setuptools.setup(
-    name="deepethogram",
-    version="0.2.0",
-    author="Jim Bohnslav",
-    author_email="jbohnslav@gmail.com",
-    description="Temporal action detection for biology",
-    long_description=long_description,
-    long_description_content_type="text/markdown",
-    include_package_data=True,
-    packages=setuptools.find_packages(),
-    classifiers=[
-        "Programming Language :: Python :: 3",
-        "Operating System :: OS Independent",
-    ],
-    entry_points={"console_scripts": ["deepethogram = deepethogram.gui.main:entry"]},
-    python_requires=">=3.7,<3.8",
-    install_requires=get_requirements(),
-    options={
-        "ruff": {
-            "target-version": "py37",
-        },
-    },
-    setup_requires=["setuptools"],
-)
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..3829aa0
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1589 @@
+version = 1
+revision = 3
+requires-python = "==3.8.*"
+resolution-markers = [
+    "platform_machine != 'aarch64' and platform_machine != 'arm64'",
+    "platform_machine == 'aarch64'",
+    "platform_machine == 'arm64'",
+]
+
+[[package]]
+name = "absl-py"
+version = "2.3.1"
+source = { registry = "https://pypi.org/simple" }
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+version = "2.4.4"
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+[[package]]
+name = "aiohttp"
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+    { name = "multidict" },
+    { name = "yarl" },
+]
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