added experiments

main.py

@@ -2,48 +2,51 @@ import matplotlib.pyplot as plt
 import saved_cordinats
 
 
-from imageai.Detection import VideoObjectDetection
+# from imageai.Detection import VideoObjectDetection
 
-vid_obj_detect = VideoObjectDetection()
-vid_obj_detect.setModelTypeAsYOLOv3()
+# vid_obj_detect = VideoObjectDetection()
+# vid_obj_detect.setModelTypeAsYOLOv3()
 
-vid_obj_detect.setModelPath(r"/home/mikolaj/2ait_tech/sportowe/film/yolo.h5")
-vid_obj_detect.loadModel()
+# vid_obj_detect.setModelPath(r"/home/mikolaj/2ait_tech/sportowe/film/yolo.h5")
+# vid_obj_detect.loadModel()
 
 
-person_points = []
-ball_points = []
+# person_points = []
+# ball_points = []
 
 
-def forFrame(frame_number, output_array, output_count, detected_frame):
-    for index, object in enumerate(output_array):
-        if object['name'] == 'sports ball':
-            ball_points.append((index, object['box_points'][0], object['box_points'][3]))
-        else:
-            person_points.append((index, object['box_points'][0], object['box_points'][3]))
+# def forFrame(frame_number, output_array, output_count, detected_frame):
+#     for index, object in enumerate(output_array):
+#         if object['name'] == 'sports ball':
+#             ball_points.append((index, object['box_points'][0], object['box_points'][1]))
+#         else:
+#             person_points.append((index, object['box_points'][0], object['box_points'][1]))
 
-detected_vid_obj = vid_obj_detect.detectObjectsFromVideo(
-    input_file_path =  r"shorted.mp4",
-    output_file_path = r"changed_shorted.mp4",
-    frames_per_second=20,
-    frame_detection_interval=20,
-    log_progress=True,
-    per_frame_function = forFrame,
-    # per_second_function=forSeconds,
-    return_detected_frame = True,
-)
+# detected_vid_obj = vid_obj_detect.detectObjectsFromVideo(
+#     input_file_path =  r"man.mp4",
+#     output_file_path = r"man_changed.mp4",
+#     frames_per_second=20,
+#     frame_detection_interval=2,
+#     log_progress=True,
+#     per_frame_function = forFrame,
+#     # per_second_function=forSeconds,
+#     return_detected_frame = True,
+# )
 
-with open('saved_cordinats', 'w') as file:
-    file.write(str(person_points))
-    file.write("\n"*3)
-    file.write(str(ball_points))
+# with open('saved_cordinats', 'w') as file:
+#     file.write(str(person_points))
+#     file.write("\n"*3)
+#     file.write(str(ball_points))
 
 
 fig = plt.figure()
 ax = fig.add_subplot(111)
 
-# person_points = saved_cordinats.persons
-# ball_points= saved_cordinats.ball
+
+ax.set_xlim([0, 960])
+ax.set_ylim([540, 0])
+person_points = saved_cordinats.persons
+ball_points= saved_cordinats.ball
 
 COLORS = ['red', 'blue', 'orange', 'pink', 'yellow', 'brown', 'white', 'magenta', 'cyan']
 LABELS = ['p1', 'p2', 'p3', 'p4', 'p5', 'p6', 'p7', 'p8', 'p9', 'p10']
@@ -101,29 +104,37 @@ persons = {
 
 
 for index, p in enumerate(person_points):
-    persons[p[0]]['x'].append(p[1])
-    persons[p[0]]['y'].append(p[2])
+    # if p[0] > 6:
+    #     continue
+
+    if index - 1 >= 0:
+        if abs(p[1] - person_points[index -1][1]) > 20:
+            continue
+        if abs(p[2] - person_points[index -1][2]) > 20:
+            continue
+
+    persons[p[0]&7]['x'].append(p[1])
+    persons[p[0]&7]['y'].append(p[2])
 
 for k, v in persons.items():
     
-    if k > 2:
-        continue
+    # if k > 6:
+    #     continue
 
     ax.plot(
             persons[k]['x'], 
             persons[k]['y'], 
-            color=COLORS[k], 
+            color=COLORS[k%7], 
             lw=2, 
-            label=LABELS[k]
+            label=LABELS[k%7]
         ) 
 
 
-
 ball_x = [x[1] for x in ball_points]
 ball_y = [x[2] for x in ball_points]
 
 ax.plot(ball_x, ball_y, color='green', lw=2, label='ball')
 ax.legend()
 
-plt.savefig('shorted_wykres.png')
+plt.savefig('man_shorted_wykres.png')
 plt.show()