fixing skip

app.py

@@ -215,38 +215,35 @@ def process_video(input_video, out_fps = 'auto', skip_frames = 5):
 
             frame = cv2.resize(frame, (int(width), int(height)))
             print('starting Frame: ', cnt)
-            if cnt*skip_frames %2==0: 
-                
-                # flip frame vertically
-                display_frame, result = inference_frame_serial(frame)
-                
-                #print(result)
-                top_pred = process_results_for_plot(predictions = result.numpy(),
-                                                    classes = classes,
-                                                    class_sizes = class_sizes_lower)
-
-                # add to last 5   
-                last_5_shark_detected[drawn_count % 5] = int(top_pred['shark_n'] > 0)
-                last_5_human_detected[drawn_count % 5] = int(top_pred['human_n'] > 0)
-                last_5_dangerous_dist[drawn_count % 5] = int(top_pred['dangerous_dist'] > 0)
-
-                top_pred['shark_sighted'] = int(np.sum(last_5_shark_detected) > 3)
-                top_pred['human_sighted'] = int(np.sum(last_5_human_detected) > 3)
-                top_pred['dangerous_dist_confirmed'] = int(np.sum(last_5_dangerous_dist) > 3)
-
-                frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-                prediction_frame = cv2.cvtColor(display_frame, cv2.COLOR_BGR2RGB)
-                
-                #
-                #video.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
-                
+            # flip frame vertically
+            display_frame, result = inference_frame_serial(frame)
+            
+            #print(result)
+            top_pred = process_results_for_plot(predictions = result.numpy(),
+                                                classes = classes,
+                                                class_sizes = class_sizes_lower)
+
+            # add to last 5   
+            last_5_shark_detected[drawn_count % 5] = int(top_pred['shark_n'] > 0)
+            last_5_human_detected[drawn_count % 5] = int(top_pred['human_n'] > 0)
+            last_5_dangerous_dist[drawn_count % 5] = int(top_pred['dangerous_dist'] > 0)
+
+            top_pred['shark_sighted'] = int(np.sum(last_5_shark_detected) > 3)
+            top_pred['human_sighted'] = int(np.sum(last_5_human_detected) > 3)
+            top_pred['dangerous_dist_confirmed'] = int(np.sum(last_5_dangerous_dist) > 3)
+
+            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            prediction_frame = cv2.cvtColor(display_frame, cv2.COLOR_BGR2RGB)
             
+            #
+            #video.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
+            
+            if cnt*skip_frames %2==0: 
                 prediction_frame = cv2.resize(prediction_frame, (int(width), int(height)))
                 frame = prediction_frame
-                frame = draw_cockpit(frame, top_pred,cnt*skip_frames)
                 
             #if  top_pred['shark_sighted'] or top_pred['shark_suspected']: 
-                
+                frame = draw_cockpit(frame, top_pred,cnt*skip_frames)
             
             
             frame = cv2.resize(frame, (int(width), int(height)))