Add Detect Parking Slot main.py file

DetectParkingSlot/main.py

+import yaml
+import numpy as np
+import cv2
+
+fn = r"./datasets/parkinglot_1_480p.mp4"
+fn_yaml = r"./datasets/parking2.yml"
+fn_out = r"./datasets/output.avi"
+config = {'save_video': False,
+          'text_overlay': True,
+          'parking_overlay': True,
+          'parking_id_overlay': False,
+          'parking_detection': True,
+          'min_area_motion_contour': 60,
+          'park_sec_to_wait': 3,
+          'start_frame': 0} 
+
+cap = cv2.VideoCapture(fn)
+video_info = {'fps':    cap.get(cv2.CAP_PROP_FPS),
+              'width':  int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
+              'height': int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)),
+              'fourcc': cap.get(cv2.CAP_PROP_FOURCC),
+              'num_of_frames': int(cap.get(cv2.CAP_PROP_FRAME_COUNT))}
+cap.set(cv2.CAP_PROP_POS_FRAMES, config['start_frame'])
+
+
+if config['save_video']:
+    fourcc = cv2.VideoWriter_fourcc('D','I','V','X')
+    out = cv2.VideoWriter(fn_out, -1, 25.0,
+                          (video_info['width'], video_info['height']))
+
+
+with open(fn_yaml, 'r') as stream:
+    parking_data = yaml.load(stream)
+parking_contours = []
+parking_bounding_rects = []
+parking_mask = []
+for park in parking_data:
+    points = np.array(park['points'])
+    rect = cv2.boundingRect(points)
+    points_shifted = points.copy()
+    points_shifted[:,0] = points[:,0] - rect[0]
+    points_shifted[:,1] = points[:,1] - rect[1]
+    parking_contours.append(points)
+    parking_bounding_rects.append(rect)
+    mask = cv2.drawContours(np.zeros((rect[3], rect[2]), dtype=np.uint8), [points_shifted], contourIdx=-1,
+                            color=255, thickness=-1, lineType=cv2.LINE_8)
+    mask = mask==255
+    parking_mask.append(mask)
+
+parking_status = [False]*len(parking_data)
+parking_buffer = [None]*len(parking_data)
+
+
+while(cap.isOpened()):   
+    spot = 0
+    occupied = 0 
+
+    video_cur_pos = cap.get(cv2.CAP_PROP_POS_MSEC) / 1000.0 
+    video_cur_frame = cap.get(cv2.CAP_PROP_POS_FRAMES)
+    ret, frame = cap.read()    
+    if ret == False:
+        print("Capture Error")
+        break
+    
+    # frame_gray = cv2.cvtColor(frame.copy(), cv2.COLOR_BGR2GRAY)
+    frame_blur = cv2.GaussianBlur(frame.copy(), (5,5), 3)
+    frame_gray = cv2.cvtColor(frame_blur, cv2.COLOR_BGR2GRAY)
+    frame_out = frame.copy()
+    
+
+    if config['parking_detection']:        
+        for ind, park in enumerate(parking_data):
+            points = np.array(park['points'])
+            rect = parking_bounding_rects[ind]
+            roi_gray = frame_gray[rect[1]:(rect[1]+rect[3]), rect[0]:(rect[0]+rect[2])]
+            # print np.std(roi_gray)
+
+            points[:,0] = points[:,0] - rect[0] 
+            points[:,1] = points[:,1] - rect[1]
+            # print np.std(roi_gray), np.mean(roi_gray)
+            status = np.std(roi_gray) < 22 and np.mean(roi_gray) > 53
+
+            if status != parking_status[ind] and parking_buffer[ind]==None:
+                parking_buffer[ind] = video_cur_pos
+
+            elif status != parking_status[ind] and parking_buffer[ind]!=None:
+                if video_cur_pos - parking_buffer[ind] > config['park_sec_to_wait']:
+                    parking_status[ind] = status
+                    parking_buffer[ind] = None
+                  
+            elif status == parking_status[ind] and parking_buffer[ind]!=None:
+                #if video_cur_pos - parking_buffer[ind] > config['park_sec_to_wait']:
+                parking_buffer[ind] = None                    
+            # print(parking_status)
+   
+    if config['parking_overlay']:                    
+        for ind, park in enumerate(parking_data):
+            points = np.array(park['points'])
+            if parking_status[ind]: 
+                color = (0,255,0)
+                spot = spot+1
+            else: 
+                color = (0,0,255)
+                occupied = occupied+1
+            cv2.drawContours(frame_out, [points], contourIdx=-1,
+                             color=color, thickness=2, lineType=cv2.LINE_8)            
+            moments = cv2.moments(points)        
+            centroid = (int(moments['m10']/moments['m00'])-3, int(moments['m01']/moments['m00'])+3)
+            cv2.putText(frame_out, str(park['id']), (centroid[0]+1, centroid[1]+1), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255,255,255), 1, cv2.LINE_AA)
+            cv2.putText(frame_out, str(park['id']), (centroid[0]-1, centroid[1]-1), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255,255,255), 1, cv2.LINE_AA)
+            cv2.putText(frame_out, str(park['id']), (centroid[0]+1, centroid[1]-1), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255,255,255), 1, cv2.LINE_AA)
+            cv2.putText(frame_out, str(park['id']), (centroid[0]-1, centroid[1]+1), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255,255,255), 1, cv2.LINE_AA)
+            cv2.putText(frame_out, str(park['id']), centroid, cv2.FONT_HERSHEY_SIMPLEX, 0.4, (0,0,0), 1, cv2.LINE_AA)
+            # print 'occupied: ', occupied
+            # print 'spot: ', spot
+
+    # Draw Overlay
+    # if config['text_overlay']:
+    #     cv2.rectangle(frame_out, (1, 5), (280, 90),(255,255,255), 85) 
+    #     str_on_frame = "Frames: %d/%d" % (video_cur_frame, video_info['num_of_frames'])
+    #     cv2.putText(frame_out, str_on_frame, (5,30), cv2.FONT_HERSHEY_SCRIPT_COMPLEX,
+    #                 0.7, (0,128,255), 2, cv2.LINE_AA)
+    #     str_on_frame = "Spot: %d Occupied: %d" % (spot, occupied)
+    #     cv2.putText(frame_out, str_on_frame, (5,90), cv2.FONT_HERSHEY_SCRIPT_COMPLEX,
+    #                         0.7, (0,128,255), 2, cv2.LINE_AA)
+
+            
+
+    if config['save_video']:
+        if video_cur_frame % 35 == 0:
+            out.write(frame_out)    
+    
+
+    cv2.imshow('Detecção de Vagas de Estacionamento', frame_out)
+    cv2.waitKey(40)
+    # cv2.imshow('background mask', bw)
+    k = cv2.waitKey(1)
+    if k == ord('q'):
+        break
+    elif k == ord('c'):
+        cv2.imwrite('frame%d.jpg' % video_cur_frame, frame_out)
+    elif k == ord('j'):
+        cap.set(cv2.CAP_PROP_POS_FRAMES, video_cur_frame+1000)
+
+cap.release()
+if config['save_video']: out.release()
+cv2.destroyAllWindows()    
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