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check plasma store and consolidate frame drawing

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This commit is contained in:
Blake Blackshear 2020-02-16 08:00:41 -06:00
parent 569e07949f
commit 80b9652f7a
4 changed files with 54 additions and 51 deletions
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14
detect_objects.py
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@ -80,6 +80,11 @@ def main():
# start plasma store
plasma_cmd = ['plasma_store', '-m', '400000000', '-s', '/tmp/plasma']
plasma_process = sp.Popen(plasma_cmd, stdout=sp.DEVNULL, stderr=sp.DEVNULL)
time.sleep(1)
rc = plasma_process.poll()
if rc is not None:
raise RuntimeError("plasma_store exited unexpectedly with "
"code %d" % (rc,))
##
# Setup config defaults for cameras
@ -95,6 +100,7 @@ def main():
# Start the shared tflite process
tflite_process = EdgeTPUProcess(MODEL_PATH)
# start the camera processes
camera_processes = []
camera_stats_values = {}
for name, config in CONFIG['cameras'].items():
@ -167,9 +173,13 @@ def main():
while True:
# max out at 1 FPS
time.sleep(1)
frame = object_processor.current_frame_with_objects(camera_name)
frame = object_processor.get_current_frame(camera_name)
if frame is None:
frame = np.zeros((720,1280,3), np.uint8)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
ret, jpg = cv2.imencode('.jpg', frame)
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
b'Content-Type: image/jpeg\r\n\r\n' + jpg.tobytes() + b'\r\n\r\n')
app.run(host='0.0.0.0', port=WEB_PORT, debug=False)

87
frigate/object_processing.py
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@ -40,51 +40,9 @@ class TrackedObjectProcessor(threading.Thread):
return self.camera_data[camera]['best_objects'][label]['frame']
else:
return None
def get_frame(self, config, camera, obj):
object_id_hash = hashlib.sha1(str.encode(f"{camera}{obj['frame_time']}"))
object_id_bytes = object_id_hash.digest()
object_id = plasma.ObjectID(object_id_bytes)
best_frame = self.plasma_client.get(object_id)
box = obj['box']
draw_box_with_label(best_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}")
# print a timestamp
if config['snapshots']['show_timestamp']:
time_to_show = datetime.datetime.fromtimestamp(obj['frame_time']).strftime("%m/%d/%Y %H:%M:%S")
cv2.putText(best_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
return best_frame
def current_frame_with_objects(self, camera):
frame_time = self.camera_data[camera]['current_frame']
object_id_hash = hashlib.sha1(str.encode(f"{camera}{frame_time}"))
object_id_bytes = object_id_hash.digest()
object_id = plasma.ObjectID(object_id_bytes)
current_frame = self.plasma_client.get(object_id)
tracked_objects = copy.deepcopy(self.camera_data[camera]['tracked_objects'])
# draw the bounding boxes on the screen
for obj in tracked_objects.values():
thickness = 2
color = COLOR_MAP[obj['label']]
if obj['frame_time'] != frame_time:
thickness = 1
color = (255,0,0)
box = obj['box']
draw_box_with_label(current_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
# # print fps
# cv2.putText(frame, str(self.fps.eps())+'FPS', (10, 60), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
# convert to BGR
frame = cv2.cvtColor(current_frame, cv2.COLOR_RGB2BGR)
# encode the image into a jpg
ret, jpg = cv2.imencode('.jpg', frame)
return jpg.tobytes()
def get_current_frame(self, camera):
return self.camera_data[camera]['current_frame']
def run(self):
while True:
@ -94,21 +52,56 @@ class TrackedObjectProcessor(threading.Thread):
best_objects = self.camera_data[camera]['best_objects']
current_object_status = self.camera_data[camera]['object_status']
self.camera_data[camera]['tracked_objects'] = tracked_objects
self.camera_data[camera]['current_frame'] = frame_time
###
# Draw tracked objects on the frame
###
object_id_hash = hashlib.sha1(str.encode(f"{camera}{frame_time}"))
object_id_bytes = object_id_hash.digest()
object_id = plasma.ObjectID(object_id_bytes)
current_frame = self.plasma_client.get(object_id)
# draw the bounding boxes on the frame
for obj in tracked_objects.values():
thickness = 2
color = COLOR_MAP[obj['label']]
if obj['frame_time'] != frame_time:
thickness = 1
color = (255,0,0)
# draw the bounding boxes on the frame
box = obj['box']
draw_box_with_label(current_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
# draw the regions on the frame
region = obj['region']
cv2.rectangle(current_frame, (region[0], region[1]), (region[2], region[3]), (0,255,0), 1)
if config['snapshots']['show_timestamp']:
time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
cv2.putText(current_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
###
# Set the current frame as ready
###
self.camera_data[camera]['current_frame'] = current_frame
###
# Maintain the highest scoring recent object and frame for each label
###
for obj in tracked_objects.values():
# if the object wasn't seen on the current frame, skip it
if obj['frame_time'] != frame_time:
continue
if obj['label'] in best_objects:
now = datetime.datetime.now().timestamp()
# if the object is a higher score than the current best score
# or the current object is more than 1 minute old, use the new object
if obj['score'] > best_objects[obj['label']]['score'] or (now - best_objects[obj['label']]['frame_time']) > 60:
obj['frame'] = self.get_frame(config, camera, obj)
obj['frame'] = np.copy(current_frame)
best_objects[obj['label']] = obj
else:
obj['frame'] = self.get_frame(config, camera, obj)
obj['frame'] = np.copy(current_frame)
best_objects[obj['label']] = obj
###

2
frigate/objects.py
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@ -9,7 +9,7 @@ import numpy as np
import multiprocessing as mp
from collections import defaultdict
from scipy.spatial import distance as dist
from frigate.util import draw_box_with_label, LABELS, calculate_region
from frigate.util import draw_box_with_label, calculate_region
# class ObjectCleaner(threading.Thread):
# def __init__(self, camera):

2
frigate/video.py
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@ -16,7 +16,7 @@ import copy
import itertools
import json
from collections import defaultdict
from frigate.util import tonumpyarray, LABELS, draw_box_with_label, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond
from frigate.util import tonumpyarray, draw_box_with_label, area, calculate_region, clipped, intersection_over_union, intersection, EventsPerSecond
# from frigate.object_detection import RegionPrepper, RegionRequester
from frigate.objects import ObjectTracker
# from frigate.mqtt import MqttObjectPublisher