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this projects helps to  show the all matched images in data with the object which is in front if camera

Author: IcodeG00D

skinned.py

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+#python project skinned with multiple faces and without gray scale
+
+
+import cv2
+
+# Define the paths of the target images
+target_image_paths = [
+'C:\\Users\\Kushagra pathak\\Desktop\\python\\testimg\\765f28e4-33d3-4a9c-be0e-4bc9e6cee4fe.jfif',
+    'C:\\Users\\Kushagra pathak\\Desktop\\python\\testimg\\93c4ec94-5e2e-4e44-9baf-6f7f43eeb5c7.jfif',
+    'C:\\Users\\Kushagra pathak\\Desktop\\python\\testimg\\d612eb6b-089c-4d91-b435-a03d51e01adf.jfif',
+     # Add more image paths as needed
+]
+
+# Create a list to store the target images and their descriptors
+target_images = []
+target_keypoints = []
+target_descriptors = []
+
+# Create a feature detector
+orb = cv2.ORB_create()
+
+# Load the target images and compute descriptors
+for path in target_image_paths:
+    target_image = cv2.imread(path)
+    keypoints_target, descriptors_target = orb.detectAndCompute(target_image, None)
+    if descriptors_target is not None:
+        target_images.append(target_image)
+        target_keypoints.append(keypoints_target)
+        target_descriptors.append(descriptors_target)
+
+# Create a feature matcher
+bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
+
+# Initialize the camera
+camera = cv2.VideoCapture(0)
+
+while True:
+    # Capture frame-by-frame
+    ret, frame = camera.read()
+
+    # Detect features in the frame
+    keypoints_frame, descriptors_frame = orb.detectAndCompute(frame, None)
+
+    best_match_idx = None  # Index of the best matching target image
+    best_match_distance = float('inf')  # Initial distance set to infinity
+
+    # Match the features between the frame and each target image
+    for i, descriptors_target in enumerate(target_descriptors):
+        matches = bf.match(descriptors_frame, descriptors_target)
+        matches = sorted(matches, key=lambda x: x.distance)
+
+        # Check if the current target image has a better match
+        if matches[0].distance < best_match_distance:
+            best_match_idx = i
+            best_match_distance = matches[0].distance
+
+    if best_match_idx is not None:
+        # Draw the best match on the frame
+        matched_frame = cv2.drawMatches(
+            frame, keypoints_frame,
+            target_images[best_match_idx], target_keypoints[best_match_idx], [matches[0]], None, flags=2
+        )
+        cv2.imshow('Object Detection', matched_frame)
+    else:
+        cv2.imshow('Object Detection', frame)
+
+    # Check for the 'q' key to exit the program
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# Release the camera and close all windows
+camera.release()
+cv2.destroyAllWindows()