def main_face_recognition(address: str) -> None:
route = "face/recognize"
test_url = f"{address}/{route}"
content_type = 'image/jpeg'
headers = {'content-type': content_type}
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
while True:
ret, frame = cap.read()
if not ret:
break
_, image_to_send = cv2.imencode('.jpg', frame)
response = requests.post(test_url,
data=image_to_send.tostring(),
headers=headers)
response_json = response.json()
boxes = response_json["faces_loc"]
ids = response_json["faces_id"]
if len(boxes) > 0:
frame = draw_bboxes(frame, boxes, ids)
cv2.imshow("test case", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def __call__(self, scene: Image) -> Image:
det_result = self.detector.predict((scene, ))[0]
boxes = det_result.boxes
keypoints = det_result.keypoints
scene = draw_keypoints(scene, keypoints)
scene = draw_bboxes(scene, boxes)
return scene
def main_person_detection(address: str) -> None:
route = "object/detection"
test_url = f"{address}/{route}"
content_type = 'image/jpeg'
headers = {'content-type': content_type}
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
while True:
ret, frame = cap.read()
if not ret:
break
_, image_to_send = cv2.imencode('.jpg', frame)
response = requests.post(test_url,
data=image_to_send.tostring(),
headers=headers)
detections = response.json()["boxes"]
boxes = detections["boxes"]
classes = detections["class_id"]
if len(boxes) > 0:
frame = draw_bboxes(frame, boxes, classes)
cv2.imshow("test case", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def __call__(self, scene: Image) -> Image:
det_result = self.detector.get_locations(scene)
scene = draw_bboxes(scene, det_result)
return scene
def __call__(self, scene: Image) -> Image:
det_results = self.detector.predict((scene, ))[0]
return draw_bboxes(scene, det_results.boxes)