手势识别服务器很快就报错 502

通过网络摄像头，每秒检测2次画面中的手势

无论我降低到多少fps，还是很快就报错502

b'\r\n502 Bad Gateway\r\n\r\n

502 Bad Gateway

直接用手势api的

import requests
import base64
import cv2
import time


def draw_rectangle(current_frame, start_pt, end_pt):
    color = (255, 0, 0)
    thickness = 2
    the_processed_frame = cv2.rectangle(current_frame, start_pt, end_pt, color, thickness)
    return the_processed_frame


request_url = "https://aip.baidubce.com/rest/2.0/image-classify/v1/gesture"
cap = cv2.VideoCapture(0)
frame_rate = 2
prev = 0
# f = open('5.jpg', 'rb')
while (True):
    time_elapsed = time.time() - prev
    ret, frame = cap.read()
    if time_elapsed > 1. / frame_rate:
        prev = time.time()
        print(prev)
        retval, buffer = cv2.imencode('.jpg', frame)
        img = base64.b64encode(buffer)
        params = {"image": img}
        access_token = '*******'
        request_url = request_url + "?access_token=" + access_token
        headers = {'content-type': 'application/x-www-form-urlencoded'}
        response = requests.post(request_url, data=params, headers=headers)
        try:
            if response.ok:
                print(response)
                display_frame = frame
                if 'result' not in response.json():
                    print(response.json())
                else:
                    result = response.json()['result']
                    for every_result in result:
                        if every_result['classname'] == 'Five':
                            print(every_result)
                            start_pt_x = every_result['left']
                            start_pt_y = every_result['top']
                            end_pt_x = every_result['width'] + start_pt_x
                            end_pt_y = every_result['height'] + start_pt_y
                            start_pt = (start_pt_x, start_pt_y)
                            end_pt = (end_pt_x, end_pt_y)
                            display_frame = draw_rectangle(frame, start_pt, end_pt)

                        else:
                            print('none')
        except:
            display_frame = frame
            print(response.content)

        cv2.imshow('frame', display_frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()