def gen(camera):
"""Video streaming generator function."""
while True:
image = camera.read()
image = cv2.resize(image,
dsize=(640, 480),
interpolation=cv2.INTER_AREA)
frame = darknet.nparray_to_image(image)
r = darknet.detect_image(net,
meta,
frame,
thresh=.5,
hier_thresh=.5,
nms=.45,
debug=False)
boxes = []
for k in range(len(r)):
width = r[k][2][2]
height = r[k][2][3]
center_x = r[k][2][0]
center_y = r[k][2][1]
bottomLeft_x = center_x - (width / 2)
bottomLeft_y = center_y - (height / 2)
x, y, w, h = bottomLeft_x, bottomLeft_y, width, height
boxes.append((x, y, w, h))
for k in range(len(boxes)):
x, y, w, h = boxes[k]
top = max(0, np.floor(x + 0.5).astype(int))
left = max(0, np.floor(y + 0.5).astype(int))
right = min(image.shape[1], np.floor(x + w + 0.5).astype(int))
bottom = min(image.shape[0], np.floor(y + h + 0.5).astype(int))
cv2.rectangle(image, (top, left), (right, bottom), (255, 0, 0), 2)
cv2.line(image, (top + int(w / 2), left),
(top + int(w / 2), left + int(h)), (0, 255, 0), 3)
cv2.line(image, (top, left + int(h / 2)),
(top + int(w), left + int(h / 2)), (0, 255, 0), 3)
cv2.circle(image, (top + int(w / 2), left + int(h / 2)), 2,
tuple((0, 0, 255)), 5)
ret, jpeg = cv2.imencode('.jpg', image)
darknet.free_image(frame)
# print("after get_frame")
if jpeg is not None:
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() +
b'\r\n')
else:
print("frame is none")
def imageDetection(image, network, class_names, class_colors, thresh):
# Modified from darknet_images.py
width = darknet.network_width(network)
height = darknet.network_height(network)
darknet_image = darknet.make_image(width, height, 3)
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image_resized = cv2.resize(image_rgb, (width, height),
interpolation=cv2.INTER_LINEAR)
darknet.copy_image_from_bytes(darknet_image, image_resized.tobytes())
detections = darknet.detect_image(network, class_names, darknet_image, thresh=thresh)
darknet.free_image(darknet_image)
image = darknet.draw_boxes(detections, image_resized, class_colors)
return cv2.cvtColor(image, cv2.COLOR_BGR2RGB), detections
def gen(camera):
# """Video streaming generator function."""
i = 0
while True:
i += 1
image = camera.read()
image = cv2.resize(image, dsize=(640, 480),
interpolation=cv2.INTER_AREA)
print(i)
# if not ret:
# break
frame = darknet.nparray_to_image(image)
r = darknet.detect_image(net, meta, frame, thresh=.5, hier_thresh=.5, nms=.45, debug=False)
print(f"r:\n{r}")
# [(b'normal', 0.9838562607765198, (337.76190185546875, 226.85903930664062, 41.72311782836914, 109.13109588623047)),
# (b'normal', 0.907978355884552, (302.71875, 253.96533203125, 41.06242752075195, 113.02967834472656)),
# (b'normal', 0.8925231695175171, (377.8631286621094, 233.21629333496094, 32.55954360961914, 110.92288970947266))]
boxes = []
for k in range(len(r)):
width = r[k][2][2]
height = r[k][2][3]
center_x = r[k][2][0]
center_y = r[k][2][1]
bottomLeft_x = center_x - (width / 2)
bottomLeft_y = center_y - (height / 2)
x, y, w, h = bottomLeft_x, bottomLeft_y, width, height
mytexts = r[k][0]
mythresh = r[k][1]
boxes.append((x, y, w, h, mytexts, mythresh))
print("next")
for k in range(len(boxes)):
x, y, w, h, texts, threshs = boxes[k]
top = max(0, np.floor(x + 0.5).astype(int))
left = max(0, np.floor(y + 0.5).astype(int))
right = min(image.shape[1], np.floor(x + w + 0.5).astype(int))
bottom = min(image.shape[0], np.floor(y + h + 0.5).astype(int))
# cv2.rectangle(image, (top, left), (right, bottom), (0, 255, 0), 1)
if texts.decode('utf-8') == 'normal':
cv2.rectangle(image, (top, left),
(right, bottom), (255, 0, 0), 2)
cv2.putText(image, texts.decode('utf-8') + '(' + str(threshs*100)
[:5] + '%)', (top, left-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0))
elif texts.decode('utf-8') == 'fighting':
cv2.rectangle(image, (top, left),
(right, bottom), (0, 0, 255), 2)
# mark probablity
cv2.putText(image, texts.decode('utf-8') + '(' + str(threshs*100)
[:5] + '%)', (top, left-5), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))
# cv2.imshow('frame', image)
ret, jpeg = cv2.imencode('.jpg', image)
# darknet dynamic allocation
darknet.free_image(frame)
if jpeg is not None:
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() + b'\r\n')
else:
print("frame is none")
def __exit__(self, type, value, traceback):
darknet.free_image(self._img)
self._img = None
center_x = r[k][2][0]
center_y = r[k][2][1]
bottomLeft_x = center_x - (width / 2)
bottomLeft_y = center_y - (height / 2)
x, y, w, h = bottomLeft_x, bottomLeft_y, width, height
boxes.append((x, y, w, h))
for k in range(len(boxes)):
x, y, w, h = boxes[k]
top = max(0, np.floor(x + 0.5).astype(int))
left = max(0, np.floor(y + 0.5).astype(int))
right = min(image.shape[1], np.floor(x + w + 0.5).astype(int))
bottom = min(image.shape[0], np.floor(y + h + 0.5).astype(int))
cv2.rectangle(image, (top, left), (right, bottom), (255, 0, 0), 2)
cv2.line(image, (top + int(w / 2), left),
(top + int(w / 2), left + int(h)), (0, 255, 0), 3)
cv2.line(image, (top, left + int(h / 2)),
(top + int(w), left + int(h / 2)), (0, 255, 0), 3)
cv2.circle(image, (top + int(w / 2), left + int(h / 2)), 2,
tuple((0, 0, 255)), 5)
cv2.imshow('frame', image)
darknet.free_image(
frame) ## darknet에서 쓰는 c언어 동적할당 해제해주는 함수(써주어야 메모리가 버틴다.)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
center_x = r[k][2][0]
center_y = r[k][2][1]
bottomLeft_x = center_x - (width / 2)
bottomLeft_y = center_y - (height / 2)
x, y, w, h = bottomLeft_x, bottomLeft_y, width, height
boxes.append((x, y, w, h))
for k in range(len(boxes)):
x, y, w, h = boxes[k]
top = max(0, np.floor(x + 0.5).astype(int))
left = max(0, np.floor(y + 0.5).astype(int))
right = min(image.shape[1], np.floor(x + w + 0.5).astype(int))
bottom = min(image.shape[0], np.floor(y + h + 0.5).astype(int))
cv2.rectangle(image, (top, left), (right, bottom), (255, 0, 0), 2)
cv2.line(image, (top + int(w / 2), left),
(top + int(w / 2), left + int(h)), (0, 255, 0), 3)
cv2.line(image, (top, left + int(h / 2)),
(top + int(w), left + int(h / 2)), (0, 255, 0), 3)
cv2.circle(image, (top + int(w / 2), left + int(h / 2)), 2,
tuple((0, 0, 255)), 5)
cv2.imshow('frame', image)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# free_image=C++ image processing library
# multi-thread 32 bit support
darknet.free_image(frame)
cap.release()
def gen(camera):
# """Video streaming generator function."""
i = 0
while True:
i += 1
image = camera.read()
image = cv2.resize(image,
dsize=(640, 480),
interpolation=cv2.INTER_AREA)
print(i)
# if not ret:
# break
frame = darknet.nparray_to_image(image)
r = darknet.detect_image(net,
meta,
frame,
thresh=.5,
hier_thresh=.5,
nms=.45,
debug=False)
print(r)
boxes = []
for k in range(len(r)):
width = r[k][2][2]
height = r[k][2][3]
center_x = r[k][2][0]
center_y = r[k][2][1]
bottomLeft_x = center_x - (width / 2)
bottomLeft_y = center_y - (height / 2)
x, y, w, h = bottomLeft_x, bottomLeft_y, width, height
mytexts = r[k][0]
mythresh = r[k][1]
boxes.append((x, y, w, h, mytexts, mythresh))
print(1)
for k in range(len(boxes)):
x, y, w, h, texts, threshs = boxes[k]
top = max(0, np.floor(x + 0.5).astype(int))
left = max(0, np.floor(y + 0.5).astype(int))
right = min(image.shape[1], np.floor(x + w + 0.5).astype(int))
bottom = min(image.shape[0], np.floor(y + h + 0.5).astype(int))
# cv2.rectangle(image, (top, left), (right, bottom), (0, 255, 0), 1)
if texts.decode('utf-8') == 'normal':
cv2.rectangle(image, (top, left), (right, bottom), (255, 0, 0),
2)
cv2.putText(
image,
texts.decode('utf-8') + '(' + str(threshs * 100)[:5] +
'%)', (top, left - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(255, 0, 0))
elif texts.decode('utf-8') == 'fighting':
cv2.rectangle(image, (top, left), (right, bottom), (0, 0, 255),
2)
cv2.putText(
image,
texts.decode('utf-8') + '(' + str(threshs * 100)[:5] +
'%)', (top, left - 5), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 0, 255))
ret, jpeg = cv2.imencode('.jpg', image)
darknet.free_image(
frame) ## darknet에서 쓰는 c언어 동적할당 해제해주는 함수(써주어야 메모리가 버틴다.)
if jpeg is not None:
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() +
b'\r\n')
else:
print("frame is none")