# from flask import Flask, request, jsonify # from flask_cors import CORS # import cv2 # import numpy as np # import base64 # app = Flask(__name__) # CORS(app, origins=["http://localhost:3000"]) # Allow requests from http://localhost:3000 # # CORS(app) # def decode_base64_image(base64_str): # header, encoded = base64_str.split(',', 1) # decoded_data = base64.b64decode(encoded) # np_data = np.frombuffer(decoded_data, np.uint8) # img = cv2.imdecode(np_data, cv2.IMREAD_COLOR) # return img # @app.route('/match-templates', methods=['POST']) # def match_templates(): # data = request.json # master_image_base64 = data['master_image'] # sub_images_base64 = data['sub_images'] # master_image = decode_base64_image(master_image_base64) # master_h, master_w, _ = master_image.shape # areas = [] # for sub_image_base64 in sub_images_base64: # sub_image = decode_base64_image(sub_image_base64) # h, w, _ = sub_image.shape # print(f"Matching template of size {w}x{h} in master image of size {master_w}x{master_h}") # # Perform template matching # result = cv2.matchTemplate(master_image, sub_image, cv2.TM_CCOEFF_NORMED) # min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) # print(f"Match result - Min Value: {min_val}, Max Value: {max_val}") # print(f"Min Location: {min_loc}, Max Location: {max_loc}") # # Define a lower threshold for the match quality # threshold = 0.5 # if max_val >= threshold: # top_left = max_loc # bottom_right = (top_left[0] + w, top_left[1] + h) # # Convert coordinates to percentages # polygon = [ # (top_left[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, bottom_right[1] / master_h * 100), # (top_left[0] / master_w * 100, bottom_right[1] / master_h * 100) # ] # areas.append({ # 'sub_image': sub_image_base64, # 'polygons': [polygon] # }) # else: # print(f"No match found with sufficient confidence for sub-image {sub_image_base64[:30]}...") # return jsonify({'areas': areas}) # if __name__ == '__main__': # app.run(debug=True) # from flask import Flask, request, jsonify # from flask_cors import CORS # import cv2 # import numpy as np # import base64 # app = Flask(__name__) # # CORS(app) # CORS(app, origins=["http://localhost:3000"]) # Allow requests from http://localhost:3000 # def decode_base64_image(base64_str): # try: # header, encoded = base64_str.split(',', 1) # decoded_data = base64.b64decode(encoded) # np_data = np.frombuffer(decoded_data, np.uint8) # img = cv2.imdecode(np_data, cv2.IMREAD_COLOR) # return img # except Exception as e: # print(f"Error decoding base64 image: {e}") # return None # @app.route('/match-templates', methods=['POST']) # def match_templates(): # try: # data = request.json # master_image_base64 = data['master_image'] # sub_images_base64 = data['sub_images'] # master_image = decode_base64_image(master_image_base64) # if master_image is None: # return jsonify({'error': 'Invalid master image data'}), 400 # master_h, master_w, _ = master_image.shape # areas = [] # for sub_image_base64 in sub_images_base64: # sub_image = decode_base64_image(sub_image_base64) # if sub_image is None: # continue # h, w, _ = sub_image.shape # # Perform template matching # result = cv2.matchTemplate(master_image, sub_image, cv2.TM_CCOEFF_NORMED) # min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) # # Define a lower threshold for the match quality # threshold = 0.5 # if max_val >= threshold: # top_left = max_loc # bottom_right = (top_left[0] + w, top_left[1] + h) # # Convert coordinates to percentages # polygon = [ # (top_left[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, bottom_right[1] / master_h * 100), # (top_left[0] / master_w * 100, bottom_right[1] / master_h * 100) # ] # areas.append({ # 'sub_image': sub_image_base64, # 'polygons': [polygon] # }) # return jsonify({'areas': areas}) # except Exception as e: # print(f"Error in /match-templates endpoint: {e}") # return jsonify({'error': 'Internal server error'}), 500 # if __name__ == '__main__': # app.run(debug=True) # from flask import Flask, request, jsonify # from flask_cors import CORS # import cv2 # import numpy as np # import base64 # import os # app = Flask(__name__) # CORS(app, origins=["http://localhost:3000"]) # Allow requests from http://localhost:3000 # def decode_base64_image(base64_str): # try: # header, encoded = base64_str.split(',', 1) # decoded_data = base64.b64decode(encoded) # np_data = np.frombuffer(decoded_data, np.uint8) # img = cv2.imdecode(np_data, cv2.IMREAD_COLOR) # if img is None: # raise ValueError("Decoded image is None") # return img # except Exception as e: # print(f"Error decoding base64 image: {e}") # return None # def draw_rectangle(image, top_left, bottom_right, index): # cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2) # cv2.putText(image, f'{index}', (top_left[0], top_left[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2) # return image # @app.route('/match-templates', methods=['POST']) # def match_templates(): # try: # data = request.json # if 'master_image' not in data or 'sub_images' not in data: # return jsonify({'error': 'Invalid input data'}), 400 # master_image_base64 = data['master_image'] # sub_images_base64 = data['sub_images'] # master_image = decode_base64_image(master_image_base64) # if master_image is None: # return jsonify({'error': 'Invalid master image data'}), 400 # master_h, master_w, _ = master_image.shape # areas = [] # for index, sub_image_base64 in enumerate(sub_images_base64): # sub_image = decode_base64_image(sub_image_base64) # if sub_image is None: # print(f"Skipping invalid sub image data at index {index}") # continue # h, w, _ = sub_image.shape # print(f"Matching template of size {w}x{h} in master image of size {master_w}x{master_h} (sub-image index: {index})") # # Perform template matching # result = cv2.matchTemplate(master_image, sub_image, cv2.TM_CCOEFF_NORMED) # min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) # print(f"Match result for sub-image index {index} - Min Value: {min_val}, Max Value: {max_val}") # print(f"Min Location: {min_loc}, Max Location: {max_loc}") # # Define a lower threshold for the match quality # threshold = 0.4 # Lower the threshold to capture more matches # if max_val >= threshold: # top_left = max_loc # bottom_right = (top_left[0] + w, top_left[1] + h) # # Draw rectangle on master image for visualization # master_image = draw_rectangle(master_image, top_left, bottom_right, index) # # Convert coordinates to percentages # polygon = [ # (top_left[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, bottom_right[1] / master_h * 100), # (top_left[0] / master_w * 100, bottom_right[1] / master_h * 100) # ] # areas.append({ # 'sub_image': sub_image_base64, # 'polygons': [polygon] # }) # else: # print(f"No match found with sufficient confidence for sub-image index {index} {sub_image_base64[:30]}...") # # Save the master image with rectangles for manual inspection # cv2.imwrite('master_image_with_matches.png', master_image) # print(f"Total matched areas: {len(areas)}") # return jsonify({'areas': areas}) # except Exception as e: # print(f"Error in /match-templates endpoint: {e}") # return jsonify({'error': 'Internal server error'}), 500 # if __name__ == '__main__': # # Ensure the output directory exists # if not os.path.exists('output'): # os.makedirs('output') # app.run(debug=True) # from flask import Flask, request, jsonify # from flask_cors import CORS # import cv2 # import numpy as np # import base64 # import os # import concurrent.futures # app = Flask(__name__) # CORS(app, origins=["http://localhost:3000"]) # Allow requests from http://localhost:3000 # def decode_base64_image(base64_str): # try: # header, encoded = base64_str.split(',', 1) # decoded_data = base64.b64decode(encoded) # np_data = np.frombuffer(decoded_data, np.uint8) # img = cv2.imdecode(np_data, cv2.IMREAD_COLOR) # if img is None: # raise ValueError("Decoded image is None") # return img # except Exception as e: # print(f"Error decoding base64 image: {e}") # return None # def draw_rectangle(image, top_left, bottom_right, index): # cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2) # cv2.putText(image, f'{index}', (top_left[0], top_left[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2) # return image # def match_template(master_image, master_w, master_h, sub_image_base64, index, threshold=0.4): # sub_image = decode_base64_image(sub_image_base64) # if sub_image is None: # print(f"Skipping invalid sub image data at index {index}") # return None # h, w, _ = sub_image.shape # print(f"Matching template of size {w}x{h} in master image of size {master_w}x{master_h} (sub-image index: {index})") # # Perform template matching # result = cv2.matchTemplate(master_image, sub_image, cv2.TM_CCOEFF_NORMED) # min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) # print(f"Match result for sub-image index {index} - Min Value: {min_val}, Max Value: {max_val}") # print(f"Min Location: {min_loc}, Max Location: {max_loc}") # if max_val >= threshold: # top_left = max_loc # bottom_right = (top_left[0] + w, top_left[1] + h) # # Convert coordinates to percentages # polygon = [ # (top_left[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, top_left[1] / master_h * 100), # (bottom_right[0] / master_w * 100, bottom_right[1] / master_h * 100), # (top_left[0] / master_w * 100, bottom_right[1] / master_h * 100) # ] # return { # 'sub_image': sub_image_base64, # 'polygons': [polygon] # } # else: # print(f"No match found with sufficient confidence for sub-image index {index} {sub_image_base64[:30]}...") # return None # @app.route('/match-templates', methods=['POST']) # def match_templates(): # try: # data = request.json # if 'master_image' not in data or 'sub_images' not in data: # return jsonify({'error': 'Invalid input data'}), 400 # master_image_base64 = data['master_image'] # sub_images_base64 = data['sub_images'] # master_image = decode_base64_image(master_image_base64) # if master_image is None: # return jsonify({'error': 'Invalid master image data'}), 400 # master_h, master_w, _ = master_image.shape # areas = [] # # Use ThreadPoolExecutor for parallel processing # with concurrent.futures.ThreadPoolExecutor() as executor: # future_to_index = { # executor.submit(match_template, master_image, master_w, master_h, sub_image_base64, index): index # for index, sub_image_base64 in enumerate(sub_images_base64) # } # for future in concurrent.futures.as_completed(future_to_index): # index = future_to_index[future] # try: # result = future.result() # if result is not None: # areas.append(result) # except Exception as e: # print(f"Error processing sub-image index {index}: {e}") # # Save the master image with rectangles for manual inspection # for area in areas: # for polygon in area['polygons']: # top_left = (int(polygon[0][0] * master_w / 100), int(polygon[0][1] * master_h / 100)) # bottom_right = (int(polygon[2][0] * master_w / 100), int(polygon[2][1] * master_h / 100)) # draw_rectangle(master_image, top_left, bottom_right, 0) # Index is not needed here # cv2.imwrite('output/master_image_with_matches.png', master_image) # print(f"Total matched areas: {len(areas)}") # return jsonify({'areas': areas}) # except Exception as e: # print(f"Error in /match-templates endpoint: {e}") # return jsonify({'error': 'Internal server error'}), 500 # if __name__ == '__main__': # # Ensure the output directory exists # if not os.path.exists('output'): # os.makedirs('output') # app.run(debug=True) import cv2 import numpy as np import base64 import os import concurrent.futures from flask import Flask, request, jsonify from flask_cors import CORS print("Starting the Flask app...") # Debugging statement app = Flask(__name__) CORS(app, origins=["http://localhost:3000"]) def decode_base64_image(base64_str): try: if ',' in base64_str: header, encoded = base64_str.split(',', 1) print(f"Header: {header}") # Debugging else: encoded = base64_str print("No header found in the base64 string") # Debugging decoded_data = base64.b64decode(encoded) np_data = np.frombuffer(decoded_data, np.uint8) img = cv2.imdecode(np_data, cv2.IMREAD_COLOR) if img is None: raise ValueError("Decoded image is None") return img except Exception as e: print(f"Error decoding base64 image: {e}") return None def draw_rectangle(image, top_left, bottom_right, index): cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2) cv2.putText(image, f'{index}', (top_left[0], top_left[1] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2) return image def match_template(master_image, master_w, master_h, sub_image_base64, index, threshold=0.4): sub_image = decode_base64_image(sub_image_base64) if sub_image is None: print(f"Skipping invalid sub image data at index {index}") return None h, w, _ = sub_image.shape print(f"Matching template of size {w}x{h} in master image of size {master_w}x{master_h} (sub-image index: {index})") # Perform template matching result = cv2.matchTemplate(master_image, sub_image, cv2.TM_CCOEFF_NORMED) min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) print(f"Match result for sub-image index {index} - Min Value: {min_val}, Max Value: {max_val}") print(f"Min Location: {min_loc}, Max Location: {max_loc}") if max_val >= threshold: top_left = max_loc bottom_right = (top_left[0] + w, top_left[1] + h) # Convert coordinates to percentages polygon = [ (top_left[0] / master_w * 100, top_left[1] / master_h * 100), (bottom_right[0] / master_w * 100, top_left[1] / master_h * 100), (bottom_right[0] / master_w * 100, bottom_right[1] / master_h * 100), (top_left[0] / master_w * 100, bottom_right[1] / master_h * 100) ] return { 'sub_image': sub_image_base64, 'polygons': [polygon] } else: print(f"No match found with sufficient confidence for sub-image index {index} {sub_image_base64[:30]}...") return None @app.route('/match-templates', methods=['POST']) def match_templates(): print("Received a request on /match-templates") # Debugging statement try: data = request.json if 'master_image' not in data or 'sub_images' not in data: return jsonify({'error': 'Invalid input data'}), 400 master_image_base64 = data['master_image'] sub_images_base64 = data['sub_images'] print(f"Master image base64: {master_image_base64[:30]}...") # Debugging master_image = decode_base64_image(master_image_base64) if master_image is None: print("Failed to decode master image") return jsonify({'error': 'Invalid master image data'}), 400 master_h, master_w, _ = master_image.shape areas = [] # Use ThreadPoolExecutor for parallel processing with concurrent.futures.ThreadPoolExecutor() as executor: future_to_index = { executor.submit(match_template, master_image, master_w, master_h, sub_image_base64, index): index for index, sub_image_base64 in enumerate(sub_images_base64) } for future in concurrent.futures.as_completed(future_to_index): index = future_to_index[future] try: result = future.result() if result is not None: areas.append(result) except Exception as e: print(f"Error processing sub-image index {index}: {e}") # Save the master image with rectangles for manual inspection for area in areas: for polygon in area['polygons']: top_left = (int(polygon[0][0] * master_w / 100), int(polygon[0][1] * master_h / 100)) bottom_right = (int(polygon[2][0] * master_w / 100), int(polygon[2][1] * master_h / 100)) draw_rectangle(master_image, top_left, bottom_right, 0) # Index is not needed here cv2.imwrite('output/master_image_with_matches.png', master_image) print(f"Total matched areas: {len(areas)}") return jsonify({'areas': areas}) except Exception as e: print(f"Error in /match-templates endpoint: {e}") return jsonify({'error': 'Internal server error'}), 500 if __name__ == '__main__': if not os.path.exists('output'): os.makedirs('output') print("Running the Flask app...") # Debugging statement app.run(debug=True)