def add_new_blobs(boxes, classes, confidences, blobs, frame, tracker, mcdf):
'''
Add new blobs or updates existing ones.
'''
matched_blob_ids = []
for i, box in enumerate(boxes):
_type = classes[i] if classes is not None else None
_confidence = confidences[i] if confidences is not None else None
_tracker = get_tracker(tracker, box, frame)
match_found = False
for _id, blob in blobs.items():
if get_overlap(box, blob.bounding_box) >= 0.6:
match_found = True
if _id not in matched_blob_ids:
blob.num_consecutive_detection_failures = 0
matched_blob_ids.append(_id)
blob.update(box, _type, _confidence, _tracker)
blob_update_log_meta = {
'label': 'BLOB_UPDATE',
'object_id': _id,
'bounding_box': blob.bounding_box,
'type': blob.type,
'type_confidence': blob.type_confidence,
}
if settings.LOG_IMAGES:
blob_update_log_meta['image'] = get_base64_image(
get_box_image(frame, blob.bounding_box))
logger.debug('Blob updated.',
extra={'meta': blob_update_log_meta})
break
if not match_found:
_blob = Blob(box, _type, _confidence, _tracker)
blob_id = generate_object_id()
blobs[blob_id] = _blob
blog_create_log_meta = {
'label': 'BLOB_CREATE',
'object_id': blob_id,
'bounding_box': _blob.bounding_box,
'type': _blob.type,
'type_confidence': _blob.type_confidence,
}
if settings.LOG_IMAGES:
blog_create_log_meta['image'] = get_base64_image(
get_box_image(frame, _blob.bounding_box))
logger.debug('Blob created.', extra={'meta': blog_create_log_meta})
blobs = _remove_stray_blobs(blobs, matched_blob_ids, mcdf)
return blobs
def add_new_blobs(boxes, classes, confidences, blobs, frame, tracker, mcdf):
'''
Add new blobs or updates existing ones.
'''
matches = _match_boxes_new(boxes, classes, confidences, blobs)
box2blob_matches = {m[0]: m[1] for m in matches}
#box2blob_matches={m[1]:m[0] for m in matches}
matched_blob_ids = set([m[1] for m in matches])
for i, box in enumerate(boxes):
_type = classes[i] if classes is not None else None
_confidence = confidences[i] if confidences is not None else None
_tracker = get_tracker(tracker, box, frame)
if i in box2blob_matches: # or use try catch?
_id = box2blob_matches[i]
blob = blobs[_id]
blob.num_consecutive_detection_failures = 0
blob.update(box, _type, _confidence, _tracker)
blob_update_log_meta = {
'label': 'BLOB_UPDATE',
'object_id': _id,
'bounding_box': blob.bounding_box,
'type': blob.type,
'type_confidence': blob.type_confidence,
}
if settings.LOG_IMAGES:
blob_update_log_meta['image'] = get_base64_image(
get_box_image(frame, blob.bounding_box))
logger.debug('Blob updated.', extra={'meta': blob_update_log_meta})
else: # not match_found for this box
_blob = Blob(box, _type, _confidence, _tracker)
blob_id = generate_object_id()
blobs[blob_id] = _blob
blog_create_log_meta = {
'label': 'BLOB_CREATE',
'object_id': blob_id,
'bounding_box': _blob.bounding_box,
'type': _blob.type,
'type_confidence': _blob.type_confidence,
}
if settings.LOG_IMAGES:
blog_create_log_meta['image'] = get_base64_image(
get_box_image(frame, _blob.bounding_box))
logger.debug('Blob created.', extra={'meta': blog_create_log_meta})
blobs = _remove_stray_blobs(blobs, matched_blob_ids, mcdf)
return blobs
def add_new_blobs(boxes, classes, confidences, blobs, frame, tracker, counting_line, line_position, mcdf):
'''
Adds new blobs or updates existing ones.
'''
matched_blob_ids = []
for i, box in enumerate(boxes):
_type = classes[i] if classes is not None else None
_confidence = confidences[i] if confidences is not None else None
_tracker = get_tracker(tracker, box, frame)
box_centroid = get_centroid(box)
match_found = False
for _id, blob in blobs.items():
if not blob.counted and get_overlap(box, blob.bounding_box) >= 0.7:
match_found = True
if _id not in matched_blob_ids:
blob.num_consecutive_detection_failures = 0
matched_blob_ids.append(_id)
blob.update(box, _type, _confidence, _tracker)
logger.debug('Blob updated.', extra={
'meta': {
'cat': 'BLOB_UPSERT',
'vehicle_id': _id,
'bounding_box': blob.bounding_box,
'type': blob.type,
'type_confidence': blob.type_confidence,
'image': get_base64_image(get_box_image(frame, blob.bounding_box)),
},
})
break
if not match_found and not is_passed_counting_line(box_centroid, counting_line, line_position):
_blob = Blob(box, _type, _confidence, _tracker)
blob_id = generate_vehicle_id()
blobs[blob_id] = _blob
logger.debug('Blob created.', extra={
'meta': {
'cat': 'BLOB_UPSERT',
'vehicle_id': blob_id,
'bounding_box': _blob.bounding_box,
'type': _blob.type,
'type_confidence': _blob.type_confidence,
'image': get_base64_image(get_box_image(frame, _blob.bounding_box)),
},
})
blobs = remove_stray_blobs(blobs, matched_blob_ids, mcdf)
return blobs
def add_new_blobs(boxes, classes, confidences, blobs, frame, tracker,
counting_line, line_position, mcdf):
# add new blobs or update existing ones
matched_blob_ids = []
for i in range(len(boxes)):
_type = classes[i] if classes != None else None
_confidence = confidences[i] if confidences != None else None
_tracker = get_tracker(tracker, boxes[i], frame)
box_centroid = get_centroid(boxes[i])
box_area = get_area(boxes[i])
match_found = False
for _id, blob in blobs.items():
if blob.counted == False and get_iou(boxes[i],
blob.bounding_box) > 0.5:
match_found = True
if _id not in matched_blob_ids:
blob.num_consecutive_detection_failures = 0
matched_blob_ids.append(_id)
blob.update(boxes[i], _type, _confidence, _tracker)
log_info(
'Blob updated.', {
'cat':
'BLOB_UPSERT',
'vehicle_id':
_id,
'bounding_box':
blob.bounding_box,
'type':
blob.type,
'type_confidence':
blob.type_confidence,
'image':
get_base64_image(
get_box_image(frame, blob.bounding_box))
})
break
if not match_found and not is_passed_counting_line(
box_centroid, counting_line, line_position):
_blob = Blob(boxes[i], _type, _confidence, _tracker)
blob_id = generate_vehicle_id()
blobs[blob_id] = _blob
log_info(
'Blob created.', {
'cat':
'BLOB_UPSERT',
'vehicle_id':
blob_id,
'bounding_box':
_blob.bounding_box,
'type':
_blob.type,
'type_confidence':
_blob.type_confidence,
'image':
get_base64_image(get_box_image(frame, _blob.bounding_box))
})
blobs = remove_stray_blobs(blobs, matched_blob_ids, mcdf)
return blobs