Posted in Python onNovember 07, 2021
【人工智能项目】Python Flask搭建yolov3目标检测系统
后端代码
from flask import Flask, request, jsonify
from PIL import Image
import numpy as np
import base64
import io
import os
from backend.tf_inference import load_model, inference
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
sess, detection_graph = load_model()
app = Flask(__name__)
@app.route('/api/', methods=["POST"])
def main_interface():
response = request.get_json()
data_str = response['image']
point = data_str.find(',')
base64_str = data_str[point:] # remove unused part like this: "data:image/jpeg;base64,"
image = base64.b64decode(base64_str)
img = Image.open(io.BytesIO(image))
if(img.mode!='RGB'):
img = img.convert("RGB")
# convert to numpy array.
img_arr = np.array(img)
# do object detection in inference function.
results = inference(sess, detection_graph, img_arr, conf_thresh=0.7)
print(results)
return jsonify(results)
@app.after_request
def add_headers(response):
response.headers.add('Access-Control-Allow-Origin', '*')
response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization')
return response
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0')
展示部分
python -m http.server
python app.py
前端展示部分
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Python Flask搭建yolov3目标检测系统详解流程
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mind_programmonkey- Original Sources -
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