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update docs and add back benchmark

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Blake Blackshear
2020-02-22 08:59:16 -06:00
parent 6ef22cf578
commit e6892d66b8
6 changed files with 62 additions and 104 deletions
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35
frigate/video.py
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@@ -350,38 +350,3 @@ def track_camera(name, config, ffmpeg_global_config, global_objects_config, dete
plasma_client.put(frame, plasma.ObjectID(object_id))
# add to the queue
detected_objects_queue.put((name, frame_time, object_tracker.tracked_objects))
# if (frames >= 700 and frames <= 1635) or (frames >= 2500):
# if (frames >= 300 and frames <= 600):
# if (frames >= 0):
# row1 = cv2.hconcat([gray, cv2.convertScaleAbs(avg_frame)])
# row2 = cv2.hconcat([frameDelta, thresh])
# cv2.imwrite(f"/lab/debug/output/{frames}.jpg", cv2.vconcat([row1, row2]))
# # cv2.imwrite(f"/lab/debug/output/resized-frame-{frames}.jpg", resized_frame)
# for region in motion_regions:
# cv2.rectangle(frame, (region[0], region[1]), (region[2], region[3]), (255,128,0), 2)
# for region in object_regions:
# cv2.rectangle(frame, (region[0], region[1]), (region[2], region[3]), (0,128,255), 2)
# for region in merged_regions:
# cv2.rectangle(frame, (region[0], region[1]), (region[2], region[3]), (0,255,0), 2)
# for box in motion_boxes:
# cv2.rectangle(frame, (box[0], box[1]), (box[2], box[3]), (255,0,0), 2)
# for detection in detections:
# box = detection[2]
# draw_box_with_label(frame, box[0], box[1], box[2], box[3], detection[0], f"{detection[1]*100}%")
# for obj in object_tracker.tracked_objects.values():
# box = obj['box']
# draw_box_with_label(frame, box[0], box[1], box[2], box[3], obj['label'], obj['id'], thickness=1, color=(0,0,255), position='bl')
# cv2.putText(frame, str(total_detections), (10, 10), cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.5, color=(0, 0, 0), thickness=2)
# cv2.putText(frame, str(frame_detections), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.5, color=(0, 0, 0), thickness=2)
# cv2.imwrite(f"/lab/debug/output/frame-{frames}.jpg", frame)
# break
# start a thread to publish object scores
# mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self)
# mqtt_publisher.start()
# create a watchdog thread for capture process
# self.watchdog = CameraWatchdog(self)