bessere Stream verarbeitung in "real time"

This commit is contained in:
Patrice 2019-04-02 00:43:07 +02:00
parent a74ece6ad5
commit 26cb3370ca
1 changed files with 10 additions and 8 deletions

View File

@ -64,11 +64,12 @@ if __name__ == "__main__":
model_path = "C:/Users/John/Desktop/ster_rcnn_inception_v2_coco_2018_01_28/ster_rcnn_inception_v2_coco_2018_01_28/ozen_inference_graph.pb" model_path = "C:/Users/John/Desktop/ster_rcnn_inception_v2_coco_2018_01_28/ster_rcnn_inception_v2_coco_2018_01_28/ozen_inference_graph.pb"
odapi = DetectorAPI(path_to_ckpt=model_path) odapi = DetectorAPI(path_to_ckpt=model_path)
threshold = 0.3 threshold = 0.3
cap = cv2.VideoCapture("./videos/example_02.mp4")
while True: while True:
cap = cv2.VideoCapture("http://69.254.67.229:8081/mjpg/video.mjpg")
r, img = cap.read() r, img = cap.read()
img = cv2.resize(img, (720, 720)) img = cv2.resize(img, (500, 500))
boxes, scores, classes, num = odapi.processFrame(img) boxes, scores, classes, num = odapi.processFrame(img)
@ -76,12 +77,13 @@ if __name__ == "__main__":
for i in range(len(boxes)): for i in range(len(boxes)):
# Class 1 represents human # Class 1 represents human
if classes[i] == 1 and scores[i] > threshold: if classes[i] == 1:
box = boxes[i] if scores[i] > threshold:
cv2.rectangle(img,(box[1],box[0]),(box[3],box[2]),(255,0,0),2) box = boxes[i]
requests.get("http://192.168.178.53/play") cv2.rectangle(img,(box[1],box[0]),(box[3],box[2]),(255,0,0),2)
else: requests.get("http://192.168.178.53/play")
requests.get("http://192.168.178.53/stop") else:
requests.get("http://192.168.178.53/stop")
cv2.imshow("preview", img) cv2.imshow("preview", img)
key = cv2.waitKey(1) key = cv2.waitKey(1)