feature: implement brightness and contrast operator

Author: chetanbarakki

imagelab-backend/app/operators/conversions/brightness_and_contrast.py

@@ -0,0 +1,42 @@
+import numpy as np
+
+from app.operators.base import BaseOperator
+
+
+class BrightnessAndContrast(BaseOperator):
+    """
+    Adjusts the brightness and contrast of an image.
+
+    Params:
+        brightnessValue (int): Additive brightness offset [-100, 100]. Clamped if out of range.
+        contrastValue (float): Multiplicative contrast scale [0.0, 3.0]. 1.0 = no change.
+    """
+
+    def compute(self, image: np.ndarray) -> np.ndarray:
+        """
+        Apply brightness and contrast adjustment.
+
+        Args:
+            image: Input uint8 NumPy ndarray (grayscale or multi-channel).
+
+        Returns:
+            Adjusted image as a uint8 NumPy ndarray of the same shape.
+        """
+        if image is None or not isinstance(image, np.ndarray) or image.size == 0:
+            raise ValueError("BrightnessAndContrast.compute: received an invalid or empty image")
+        try:
+            brightness = int(self.params.get("brightnessValue", 0))
+        except (TypeError, ValueError):
+            brightness = 0
+        try:
+            contrast = float(self.params.get("contrastValue", 1.0))
+        except (TypeError, ValueError):
+            contrast = 1.0
+
+        # Ensure brightness and contrast values are within valid ranges
+        # Clamp to match frontend field_number constraints in conversions.blocks.ts
+        brightness = max(-100, min(100, brightness))
+        contrast = max(0.0, min(3.0, contrast))
+
+        adjusted = contrast * (image.astype(np.float32) - 128.0) + 128.0 + brightness
+        return np.clip(adjusted, 0, 255).astype(np.uint8)

imagelab-backend/app/operators/registry.py

@@ -10,6 +10,7 @@
 from app.operators.conversions.bgr_to_hsv import BgrToHsv
 from app.operators.conversions.bgr_to_lab import BgrToLab
 from app.operators.conversions.bgr_to_ycrcb import BgrToYcrcb
+from app.operators.conversions.brightness_and_contrast import BrightnessAndContrast
 from app.operators.conversions.channel_split import ChannelSplit
 from app.operators.conversions.clahe import claheImage
 from app.operators.conversions.color_maps import ColorMaps
@@ -79,6 +80,7 @@
     "imageconvertions_bgrtoycrcb": BgrToYcrcb,
     "imageconvertions_ycrcbtobgr": YcrcbToBgr,
     "imageconvertions_invertimage": InvertImage,
+    "imageconvertions_brightnessandcontrast": BrightnessAndContrast,
     # Drawing
     "drawingoperations_drawline": DrawLine,
     "drawingoperations_drawcircle": DrawCircle,

imagelab-backend/app/utils/color.py

@@ -1,6 +1,5 @@
 import re
 
-
 HEX_COLOR_RE = re.compile(r"^[0-9a-fA-F]{6}$")
 
 
@@ -19,17 +18,13 @@ def hex_to_bgr(hex_color: str) -> tuple[int, int, int]:
         ValueError: If hex_color is not a valid 6-digit hex color string.
     """
     if not isinstance(hex_color, str):
-        raise TypeError(
-            f"hex_to_bgr expects a str, got {type(hex_color).__name__!r}"
-        )
+        raise TypeError(f"hex_to_bgr expects a str, got {type(hex_color).__name__!r}")
 
     original = hex_color
     normalized = hex_color.removeprefix("#")
 
     if not HEX_COLOR_RE.fullmatch(normalized):
-        raise ValueError(
-            f"Invalid hex color: {original!r}. Expected format '#rrggbb' or 'rrggbb'."
-        )
+        raise ValueError(f"Invalid hex color: {original!r}. Expected format '#rrggbb' or 'rrggbb'.")
 
     r = int(normalized[0:2], 16)
     g = int(normalized[2:4], 16)

imagelab-backend/tests/test_filtering_operators.py

@@ -80,9 +80,7 @@ def test_asymmetric_kernel_uses_width_height_convention(self):
         image = np.arange(75, dtype=np.uint8).reshape(5, 5, 3)
         width, height = 1, 5
 
-        result = BoxFilter({"width": width, "height": height, "depth": -1}).compute(
-            image
-        )
+        result = BoxFilter({"width": width, "height": height, "depth": -1}).compute(image)
         expected = cv2.boxFilter(
             image,
             -1,

imagelab-frontend/eslint.config.js

@@ -19,5 +19,8 @@ export default defineConfig([
       ecmaVersion: 2020,
       globals: globals.browser,
     },
+    rules: {
+      'no-delete-var': 'off',
+    },
   },
 ])

imagelab-frontend/package-lock.json

@@ -27,6 +27,8 @@
   "devDependencies": {
     "@eslint/js": "^9.39.1",
     "@tailwindcss/vite": "^4.2.0",
+    "@testing-library/dom": "^10.4.1",
+    "@testing-library/react": "^16.3.2",
     "@types/node": "^24.10.1",
     "@types/react": "^19.2.14",
     "@types/react-dom": "^19.2.3",
@@ -42,4 +44,4 @@
     "vite": "^7.3.1",
     "vitest": "~4.0.17"
   }
-}
+}

imagelab-frontend/package.json

@@ -51,6 +51,7 @@ export const categories: CategoryInfo[] = [
       { type: "imageconvertions_bgrtoycrcb", label: "BGR to YCrCb" },
       { type: "imageconvertions_ycrcbtobgr", label: "YCrCb to BGR" },
       { type: "imageconvertions_invertimage", label: "Invert Image" },
+      { type: "imageconvertions_brightnessandcontrast", label: "Brightness and Contrast" },
     ],
   },
   {

imagelab-frontend/src/blocks/categories.ts

@@ -90,6 +90,20 @@ export const conversionsBlocks = [
     tooltip:
       "Apply different color maps to an image - Transforms the colors of an image using various color maps. This can enhance visual contrast and highlight specific features. For example, the 'JET' colormap transitions from blue to red, while 'HSV' represents hue, saturation, and value. Choose a colormap that best suits your image analysis needs.",
   },
+  {
+    type: "imageconvertions_brightnessandcontrast",
+    message0: "Adjust image brightness by %1 and contrast scale by %2",
+    args0: [
+      { type: "field_number", name: "brightnessValue", value: 0, min: -100, max: 100 },
+      { type: "field_number", name: "contrastValue", value: 1.0, min: 0.0, max: 3.0 },
+    ],
+    inputsInline: false,
+    previousStatement: null,
+    nextStatement: null,
+    style: "conversions_style",
+    tooltip:
+      "Adjusts the brightness and contrast of an image - Brightness controls the overall lightness or darkness of an image, while contrast controls the difference in intensity between different parts of the image. Increasing brightness makes the image lighter, and increasing contrast makes the differences between light and dark areas more pronounced.",
+  },
   {
     type: "imageconvertions_colortobinary",
     message0: