HSV Filter Tool

 allows users to interactively select an HSV color range from an image using trackbars and outputs the selected HSV values. Useful for finding thresholds for basic color filtration when trying to detect an object in an image

Author: avyukth-fll

computer_vision/hsv_threshold

@@ -0,0 +1,135 @@
+"""
+HSV Filter Tool
+
+This module allows the user to interactively select an HSV color range
+from an image using trackbars and outputs the selected HSV values.
+
+Dependencies:
+- OpenCV (cv2)
+- NumPy
+
+Usage:
+1. Set `IMAGE_PATH` to your image file.
+2. Run the script.
+3. Adjust the trackbars to select the desired HSV range.
+4. Press Enter to print the HSV lower and upper bounds.
+"""
+
+import cv2
+import numpy as np
+
+IMAGE_PATH = r"C:\Users\username\New folder\your_image.png"
+
+
+def load_image(path: str) -> np.ndarray:
+    """
+    Load an image from the specified path.
+
+    Parameters
+    ----------
+    path : str
+        Path to the image file.
+
+    Returns
+    -------
+    np.ndarray
+        Loaded BGR image.
+
+    Raises
+    ------
+    FileNotFoundError
+        If the image cannot be loaded.
+    """
+    image = cv2.imread(path)
+    if image is None:
+        raise FileNotFoundError(f"Failed to load image at path: {path}")
+    return image
+
+
+def create_hsv_trackbars(window_name: str) -> None:
+    """
+    Create HSV trackbars for filtering.
+
+    Parameters
+    ----------
+    window_name : str
+        Name of the OpenCV window.
+    """
+    cv2.createTrackbar("H Lower", window_name, 0, 179, lambda x: None)
+    cv2.createTrackbar("S Lower", window_name, 0, 255, lambda x: None)
+    cv2.createTrackbar("V Lower", window_name, 0, 255, lambda x: None)
+    cv2.createTrackbar("H Upper", window_name, 179, 179, lambda x: None)
+    cv2.createTrackbar("S Upper", window_name, 255, 255, lambda x: None)
+    cv2.createTrackbar("V Upper", window_name, 255, 255, lambda x: None)
+
+
+def get_hsv_bounds(window_name: str) -> tuple[np.ndarray, np.ndarray]:
+    """
+    Read the HSV lower and upper bounds from the trackbars.
+
+    Parameters
+    ----------
+    window_name : str
+        Name of the OpenCV window.
+
+    Returns
+    -------
+    tuple[np.ndarray, np.ndarray]
+        Lower and upper HSV bounds as NumPy arrays.
+    """
+    lower_bound = np.array([
+        cv2.getTrackbarPos("H Lower", window_name),
+        cv2.getTrackbarPos("S Lower", window_name),
+        cv2.getTrackbarPos("V Lower", window_name),
+    ])
+    upper_bound = np.array([
+        cv2.getTrackbarPos("H Upper", window_name),
+        cv2.getTrackbarPos("S Upper", window_name),
+        cv2.getTrackbarPos("V Upper", window_name),
+    ])
+    return lower_bound, upper_bound
+
+
+def main() -> None:
+    """
+    Main function to run the HSV filter tool.
+
+    Opens the image, creates trackbars, shows filtered results,
+    and prints the final HSV bounds when Enter is pressed.
+    """
+    try:
+        image = load_image(IMAGE_PATH)
+    except FileNotFoundError as e:
+        print(e)
+        return
+
+    window_name = "HSV Filter"
+    cv2.namedWindow(window_name)
+    create_hsv_trackbars(window_name)
+
+    while True:
+        hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+
+        lower, upper = get_hsv_bounds(window_name)
+
+        mask = cv2.inRange(hsv_image, lower, upper)
+        filtered_result = cv2.bitwise_and(image, image, mask=mask)
+
+        cv2.imshow("Original", image)
+        cv2.imshow("Filtered", filtered_result)
+
+        key = cv2.waitKey(1) & 0xFF
+        if key == 13:  # Enter key
+            print(f"HSV Range (Lower): {lower}")
+            print(f"HSV Range (Upper): {upper}")
+            print(
+                f"CSV Format: {lower[0]},{lower[1]},{lower[2]},"
+                f"{upper[0]},{upper[1]},{upper[2]}"
+            )
+            break
+
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    main()