Plot profile

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="stackview",
-    version="0.19.1",
+    version="0.19.2",
     license="BSD-3-Clause",
     author="Robert Haase",
     author_email="robert.haase@uni-leipzig.de",
@@ -15,7 +15,7 @@
     url="https://github.com/haesleinhuepf/stackview/",
     packages=setuptools.find_packages(),
     include_package_data=True,
-    install_requires=["numpy!=1.19.4", "ipycanvas", "ipywidgets", "scikit-image", "ipyevents", "toolz", "matplotlib", "ipykernel", "imageio", "ipympl", "wordcloud"],
+    install_requires=["numpy!=1.19.4", "ipycanvas", "ipywidgets", "scikit-image", "ipyevents", "toolz", "matplotlib", "ipykernel", "imageio", "ipympl", "wordcloud", "scipy"],
     python_requires='>=3.6',
     classifiers=[
         "Programming Language :: Python :: 3",

stackview/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.19.1"
+__version__ = "0.19.2"
 
 from ._static_view import jupyter_displayable_output, insight
 from ._utilities import merge_rgb
@@ -27,3 +27,5 @@
 from ._histogram import histogram
 from ._blend import blend
 from ._zoom import zoom
+from ._add_text import add_text
+from ._plot_profile import plot_profile

stackview/_add_text.py

@@ -0,0 +1,114 @@
+import numpy as np
+from typing import List, Union
+
+def add_text(
+    images: Union[List[np.ndarray], np.ndarray],
+    texts: List[str],
+    font_size: int = 16,
+    text_color: str = 'white',
+    bg_color: str = 'black',
+    position: str = 'top',
+    colormap: str = 'Greys_r'
+) -> List[np.ndarray]:
+    """
+    Burn text onto images using matplotlib.
+
+    Parameters:
+    -----------
+    images : list of np.ndarray or np.ndarray
+        List of images or n-dimensional array where first dimension is images
+    texts : list of str
+        List of text strings to burn onto each image
+    font_size : int
+        Font size for the text (default: 16)
+    text_color : str
+        Color of the text (default: 'white')
+    position : str
+        Text position: 'top', 'bottom', 'center', 'top-left', 'top-right', 
+        'bottom-left', 'bottom-right', 'center-left', 'center-right' (default: 'top')
+    colormap : str
+        Colormap to use for displaying the image (default: 'Greys_r')
+
+    Returns:
+    --------
+    list of np.ndarray
+        List of images with text burned in
+    """
+    import matplotlib.pyplot as plt
+    from matplotlib.backends.backend_agg import FigureCanvasAgg
+
+    # Convert to list if numpy array
+    if isinstance(images, np.ndarray):
+        images = [images[i] for i in range(images.shape[0])]
+
+    if len(images) != len(texts):
+        raise ValueError(f"Number of images ({len(images)}) must match number of texts ({len(texts)})")
+
+    result_images = []
+
+    for img, text in zip(images, texts):
+        # Create figure with exact image size
+        h, w = img.shape[:2]
+        dpi = 100
+        fig = plt.figure(figsize=(w/dpi, h/dpi), dpi=dpi)
+        ax = fig.add_axes([0, 0, 1, 1])
+        ax.axis('off')
+
+        # Display the image
+        ax.imshow(img, cmap=colormap)
+
+        # Determine text position
+        # Default to center
+        x_pos, y_pos = 0.5, 0.5
+        ha, va = 'center', 'center'
+
+        # Vertical positioning
+        if 'top' in position:
+            y_pos, va = 0.95, 'top'
+        elif 'bottom' in position:
+            y_pos, va = 0.05, 'bottom'
+
+        # Horizontal positioning
+        if 'left' in position:
+            x_pos, ha = 0.05, 'left'
+        elif 'right' in position:
+            x_pos, ha = 0.95, 'right'
+
+        # Add text with background
+        px = 1.0 / w
+        for delta_x, delta_y in [(-px, -px), (px, -px), (-px, px), (px, px)]:
+            ax.text(
+                x_pos+delta_x, y_pos+delta_y, text,
+                transform=ax.transAxes,
+                fontsize=font_size,
+                color=bg_color,
+                ha=ha,
+                va=va
+            )
+        ax.text(
+            x_pos, y_pos, text,
+            transform=ax.transAxes,
+            fontsize=font_size,
+            color=text_color,
+            ha=ha,
+            va=va
+        )
+
+        # Convert figure to numpy array
+        canvas = FigureCanvasAgg(fig)
+        canvas.draw()
+        buf = canvas.buffer_rgba()
+        result = np.asarray(buf)
+
+        # Convert RGBA to RGB if original was RGB
+        if img.ndim == 3 and img.shape[2] == 3:
+            result = result[:, :, :3]
+        # Convert back to single-channel if original was single-channel
+        elif img.ndim == 2 or img.shape[-1] not in [3, 4]:
+            result = result[:, :, 0]
+        result = result.astype(img.dtype)
+
+        result_images.append(result)
+        plt.close(fig)
+
+    return result_images

stackview/_bia_bob_plugins.py

@@ -36,6 +36,14 @@ def list_bia_bob_plugins():
     * Allows switching between multiple images and displaying them with a slider.
       stackview.switch(images:list)
 
+    * Add bounding boxes to an image.
+      bounding_boxes = [ {'x':5, 'y':5, 'width':10, 'height':15} ]
+      stackview.add_bounding_boxes(image, bounding_boxes)
+
+    * Add text to images at specified positions.
+      texts = ["Sample Text"] # List of texts for each image
+      stackview.add_text([image], texts, position='top-left')
+
     * Allows plotting a scatterplot of a pandas dataframe while interactively choosing the columns and using a lasso tool for selecting data points
       stackview.scatterplot(dataframe, column_x, column_y, selection_column)
 

stackview/_plot_profile.py

@@ -0,0 +1,73 @@
+def plot_profile(image, point1, point2, linecolor='orange'):
+    """
+    Extract intensity along a line between two points and create a combined figure.
+
+    Parameters:
+    -----------
+    image : numpy.ndarray
+        Input image (2D grayscale or 3D RGB)
+    point1 : tuple
+        First point coordinates (x, y)
+    point2 : tuple
+        Second point coordinates (x, y)
+    linecolor : str
+        Color for the line and points on the image and the intensity profile plot
+
+    Returns:
+    --------
+    numpy.ndarray
+        Combined figure as a numpy array (RGB image)
+    """
+    import numpy as np
+    import matplotlib.pyplot as plt
+    from scipy import ndimage
+    from matplotlib.backends.backend_agg import FigureCanvasAgg
+
+    x1, y1 = point1
+    x2, y2 = point2
+
+    # Calculate number of points along the line
+    length = int(np.hypot(x2 - x1, y2 - y1))
+
+    # Generate coordinates along the line
+    x_coords = np.linspace(x1, x2, length)
+    y_coords = np.linspace(y1, y2, length)
+
+    # Extract intensity values along the line
+    if image.ndim == 2:  # Grayscale image
+        intensities = ndimage.map_coordinates(image, [y_coords, x_coords], order=1)
+    else:  # RGB image - use average of channels or first channel
+        intensities = ndimage.map_coordinates(
+            np.mean(image, axis=2), [y_coords, x_coords], order=1
+        )
+
+    # Create figure with two subplots
+    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 5))
+
+    # Plot the image with the line
+    if image.ndim == 2:
+        ax1.imshow(image, cmap='gray')
+    else:
+        ax1.imshow(image)
+
+    ax1.plot([x1, x2], [y1, y2], '-', color=linecolor, linewidth=2, label='Profile Line')
+    ax1.plot([x1, x2], [y1, y2], 'o', color=linecolor, markersize=8)
+    ax1.axis('off')
+
+    # Plot the intensity profile
+    ax2.plot(intensities, linewidth=2, color=linecolor)
+    ax2.set_xlabel('Distance along line (pixels)')
+    ax2.set_ylabel('Intensity')
+    ax2.grid(True, alpha=0.3)
+
+    plt.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0.05)
+
+    # Convert figure to numpy array
+    canvas = FigureCanvasAgg(fig)
+    canvas.draw()
+    buf = canvas.buffer_rgba()
+    result = np.asarray(buf)
+
+    plt.close(fig)  # Close figure to prevent displaying
+
+    return result