def process(path, label, threshold, scores, debug_path):
clips = []
if os.path.isdir(path):
files = os.listdir(path)
files.sort()
clips = [os.path.join(path, file) for file in files]
elif os.path.isfile(path):
clips.append(path)
json_config = {
"mqtt": {
"host": "mqtt"
},
"cameras": {
"camera": {
"ffmpeg": {
"inputs": [{
"path": "path.mp4",
"global_args": "",
"input_args": "",
"roles": ["detect"],
}]
},
"height": 1920,
"width": 1080,
}
},
}
results = []
for c in clips:
logger.info(c)
frame_shape = get_frame_shape(c)
json_config["cameras"]["camera"]["height"] = frame_shape[0]
json_config["cameras"]["camera"]["width"] = frame_shape[1]
json_config["cameras"]["camera"]["ffmpeg"]["inputs"][0]["path"] = c
config = FrigateConfig(config=FRIGATE_CONFIG_SCHEMA(json_config))
process_clip = ProcessClip(c, frame_shape, config)
process_clip.load_frames()
process_clip.process_frames(objects_to_track=[label])
results.append((c, process_clip.top_object(debug_path)))
if not scores is None:
with open(scores, "w") as writer:
for result in results:
writer.write(f"{result[0]},{result[1]['top_score']}\n")
positive_count = sum(1 for result in results
if result[1]["object_detected"])
print(
f"Objects were detected in {positive_count}/{len(results)}({positive_count/len(results)*100:.2f}%) clip(s)."
)
def process(path, label, threshold, scores, debug_path):
clips = []
if os.path.isdir(path):
files = os.listdir(path)
files.sort()
clips = [os.path.join(path, file) for file in files]
elif os.path.isfile(path):
clips.append(path)
json_config = {
'mqtt': {
'host': 'mqtt'
},
'cameras': {
'camera': {
'ffmpeg': {
'inputs': [
{ 'path': 'path.mp4', 'global_args': '', 'input_args': '', 'roles': ['detect'] }
]
},
'height': 1920,
'width': 1080
}
}
}
results = []
for c in clips:
logger.info(c)
frame_shape = get_frame_shape(c)
json_config['cameras']['camera']['height'] = frame_shape[0]
json_config['cameras']['camera']['width'] = frame_shape[1]
json_config['cameras']['camera']['ffmpeg']['inputs'][0]['path'] = c
config = FrigateConfig(config=FRIGATE_CONFIG_SCHEMA(json_config))
process_clip = ProcessClip(c, frame_shape, config)
process_clip.load_frames()
process_clip.process_frames(objects_to_track=[label])
results.append((c, process_clip.top_object(debug_path)))
if not scores is None:
with open(scores, 'w') as writer:
for result in results:
writer.write(f"{result[0]},{result[1]['top_score']}\n")
positive_count = sum(1 for result in results if result[1]['object_detected'])
print(f"Objects were detected in {positive_count}/{len(results)}({positive_count/len(results)*100:.2f}%) clip(s).")
def test_minimal(self):
FRIGATE_CONFIG_SCHEMA(self.minimal)
def test_empty(self):
FRIGATE_CONFIG_SCHEMA({})