商品识别双十一活动

import cv2
import numpy as np

# 加载预训练模型
net = cv2.dnn.readNetFromCaffe("deploy.prototxt", "model.caffemodel")

def recognize_product(image_path):
    # 读取图像
    image = cv2.imread(image_path)
    (h, w) = image.shape[:2]
    
    # 创建输入Blob并进行前向传播
    blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
    net.setInput(blob)
    detections = net.forward()
    
    # 处理检测结果
    for i in range(0, detections.shape[2]):
        confidence = detections[0, 0, i, 2]
        if confidence > 0.5:
            box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
            (startX, startY, endX, endY) = box.astype("int")
            label = "{}: {:.2f}%".format("Product", confidence * 100)
            cv2.rectangle(image, (startX, startY), (endX, endY), (0, 255, 0), 2)
            y = startY - 15 if startY - 15 > 15 else startY + 15
            cv2.putText(image, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
    
    # 显示结果
    cv2.imshow("Product Recognition", image)
    cv2.waitKey(0)

# 测试识别功能
recognize_product("path_to_your_image.jpg")