def run_camera(input_shape, model):
num_classes = 21
conf_thresh = 0.5
bbox_util = BBoxUtility(num_classes)
vid = cv2.VideoCapture(0)
sleep(1.0)
# Compute aspect ratio of video
vidw = vid.get(cv2.CAP_PROP_FRAME_WIDTH)
vidh = vid.get(cv2.CAP_PROP_FRAME_HEIGHT)
trackers = Tracker()
while True:
ret, origin_image = vid.read()
frame = origin_image
if not ret:
print("Done!")
return None
im_size = (input_shape[0], input_shape[1])
resized = cv2.resize(frame, im_size)
rgb = cv2.cvtColor(resized, cv2.COLOR_BGR2RGB)
inputs = [image.img_to_array(rgb)]
tmp_inp = np.array(inputs)
x = preprocess_input(tmp_inp)
y = model.predict(x)
results = bbox_util.detection_out(y)
if len(results) > 0 and len(results[0]) > 0:
det_label = results[0][:, 0]
det_conf = results[0][:, 1]
det_xmin = results[0][:, 2]
det_ymin = results[0][:, 3]
det_xmax = results[0][:, 4]
det_ymax = results[0][:, 5]
top_indices = [i for i, conf in enumerate(det_conf) if conf >= conf_thresh]
top_conf = det_conf[top_indices]
top_label_indices = det_label[top_indices].tolist()
top_xmin = det_xmin[top_indices]
top_ymin = det_ymin[top_indices]
top_xmax = det_xmax[top_indices]
top_ymax = det_ymax[top_indices]
if 15 not in top_label_indices:
pass
else:
trackers.bbox = []
trackers.features_current = []
trackers.index = []
for i in range(top_conf.shape[0]):
class_num = int(top_label_indices[i])
if class_num == 15:
xmin = int(round((top_xmin[i] * vidw) * 0.9))
ymin = int(round((top_ymin[i] * vidh) * 0.9))
xmax = int(round((top_xmax[i] * vidw) * 1.1)) if int(round(
(top_xmax[i] * vidw)) * 1.1) <= vidw else int(round(
top_xmax[i] * vidw))
ymax = int(round((top_ymax[i] * vidh) * 1.1)) if int(round(
(top_ymax[i] * vidh) * 1.1)) <= vidh else int(round(top_ymax[i] * vidh))
trackers.bbox.append([xmin, ymin, xmax, ymax])
trackers.features_current.append(
Extract_feature(cv2.resize(frame[ymin:ymax, xmin:xmax, :], (32, 32))))
if trackers.features_previous is None:
trackers.index.append(i for i in range(len(trackers.bbox)))
for j in range(len(trackers.features_current)):
cv2.rectangle(frame, (int(trackers.bbox[j][0]), int(trackers.bbox[j][1])),
(int(trackers.bbox[j][2]), int(trackers.bbox[j][3])), (255, 0, 0), 2)
cv2.putText(frame, "person: {}".format(trackers.index[j] + 1),
(trackers.bbox[j][0] + 10, trackers.bbox[j][1] + 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 1)
else:
trackers.match()
trackers.update()
for j in range(len(trackers.features_current)):
cv2.rectangle(frame, (int(trackers.bbox[j][0]), int(trackers.bbox[j][1])),
(int(trackers.bbox[j][2]), int(trackers.bbox[j][3])), (255, 0, 0), 2)
cv2.putText(frame, "person: {}".format(trackers.index[j] + 1),
(trackers.bbox[j][0] + 10, trackers.bbox[j][1] + 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 1)
cv2.imshow('tracking', frame)
if cv2.waitKey(5) & 0xFF == ord('q'):
break
