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import gradio as gr | |
import json | |
import base64 | |
import requests | |
import cv2 | |
def hand_classification(img): | |
# 可选的请求参数 | |
# top_num: 返回的分类数量,不声明的话默认为 6 个 | |
PARAMS = {"top_num": 2} | |
# 服务详情 中的 接口地址 | |
MODEL_API_URL = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/classification/handclass" | |
# 调用 API 需要 ACCESS_TOKEN。若已有 ACCESS_TOKEN 则于下方填入该字符串 | |
# 否则,留空 ACCESS_TOKEN,于下方填入 该模型部署的 API_KEY 以及 SECRET_KEY,会自动申请并显示新 ACCESS_TOKEN | |
ACCESS_TOKEN = "" | |
API_KEY = "TPhSFQU5i8tYivTgsLWBRLi9" | |
SECRET_KEY = "eZbQHnOqTGYBVDXGTqzAy5kvU03t32Qz" | |
print("1. 读取目标图片 ") | |
success,encoded_image = cv2.imencode(".jpg",img) #注意这句编码,否则图像质量不合格 | |
img_test = base64.b64encode(encoded_image) | |
PARAMS["image"] = img_test.decode('UTF8') | |
if not ACCESS_TOKEN: | |
print("2. ACCESS_TOKEN 为空,调用鉴权接口获取TOKEN") | |
auth_url = "https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={}&client_secret={}".format(API_KEY, SECRET_KEY) | |
auth_resp = requests.get(auth_url) | |
auth_resp_json = auth_resp.json() | |
ACCESS_TOKEN = auth_resp_json["access_token"] | |
print("新 ACCESS_TOKEN: {}".format(ACCESS_TOKEN)) | |
else: | |
print("2. 使用已有 ACCESS_TOKEN") | |
print("3. 向模型接口 'MODEL_API_URL' 发送请求") | |
request_url = "{}?access_token={}".format(MODEL_API_URL, ACCESS_TOKEN) | |
response = requests.post(url=request_url, json=PARAMS) | |
response_json = response.json() | |
response_str = json.dumps(response_json, indent=4, ensure_ascii=False) | |
print("结果:\n{}".format(response_str)) | |
result = response_json["results"] | |
res = {result[0]["name"]:result[0]["score"],result[1]["name"]:result[1]["score"]} | |
return res | |
demo = gr.Interface(fn=hand_classification, inputs="image", outputs="label") | |
gr.close_all() | |
demo.launch() | |