python实现人工智能识别水果

from keras.applications.resnet50 import ResNet50  #//导入AI软件平台keras 里的AI模型　ResNet50
from keras.preprocessing import image#//导入图像处理库　ｉｍａｇｅ
from keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np

#//载入模型
model = ResNet50(weights='imagenet')  #//使model指向ResNet50模型
img_path = '鸟.jpg'     #//等待识别的图像(可用车，水果等)，注：需把图片放该代码的同目录下
img = image.load_img(img_path, target_size=(224, 224))   #//载入图像
    #//-图像的预处理
x = image.img_to_array(img)     #//把图像转换为数组
x = np.expand_dims(x, axis=0)   #//沿轴0(行)扩展 -> 多维数组
x = preprocess_input(x)         #//做输入预处理

#//预测
preds = model.predict(x)  #//运行模型进行预测
print('Predicted:', decode_predictions(preds, top=3)[0])  #//解码预测，输出结果

import cv2
from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np

img_path = 'capyure.jpg'


def capture_camera_pic():
cv2.namedWindow('capture_pic')
cp = cv2.VideoCapture(0)  # //指定摄像头，默认0指向第一个
while cp.isOpened():  # //检测摄像头是否打开，如果摄像头能成功打开，则进行循环的视频拍照显示
    ok, frame = cp.read()  # 读取一帧数据
    if not ok:  # 如果拍照失败，退出
        break


    cv2.imwrite(img_path, frame)  # 保存图像

    # 翻译
    # translator = Translator(to_lang='chinese')
    # translation = translator.translate(jieguo())

    cv2.putText(frame, jieguo(), (30, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 0, 0), 4)
    cv2.imshow('capture_pic', frame)  # 显示图像
    c = cv2.waitKey(10)
    if c & 0xff == ord('q'):
        break
cp.release()
cv2.destroyAllWindows()


def jieguo():
model = ResNet50(weights='imagenet')
img_path = 'capyure.jpg'
img = image.load_img(img_path, target_size=(224, 224))

x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
preds = model.predict(x)

return decode_predictions(preds, top=3)[0][0][1];


if __name__ == '__main__':
capture_camera_pic()
｝

改进为可以把文字由英文转中文的代码：
import cv2
from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input,decode_predictions
import  numpy  as np
from translate import  Translator
from PIL import Image, ImageDraw, ImageFont
#调用摄像头
img_path='capyure.jpg'
def capture_camera_pic():
cv2.namedWindow('capture_pic')
cp=cv2.VideoCapture(0) #//指定摄像头，默认0指向第一个
while cp.isOpened():      #//检测摄像头是否打开，如果摄像头能成功打开，则进行循环的视频拍照显示
    ok,frame=cp.read()   #读取一帧数据
    if not ok:    #如果拍照失败，退出
        break


    cv2.imwrite(img_path,frame)  #保存图像
    #cv2.putText(frame,jieguo(),(30,50),cv2.FONT_HERSHEY_COMPLEX,1,(255,0,0),4)
    #cv2.putText(frame,jieguo(),(30,50), cv2.FONT_HERSHEY_SCRIPT_SIMPLEX,1,(255,0,0),4)
    change()
   # change_cv2_draw(frame, jieguo(), (0,0), 20, (255, 0, 0))
   # cv2ImgAddText(frame, "封", 10, 65, (255, 0, 0), 20)
    #//cv2.imshow('capture_pic',frame)         #显示图像
    c=cv2.waitKey(5)
    if c & 0xff == ord('q'):


     break
cp.release()
cv2.destroyAllWindows()


def jieguo():
       model = ResNet50(weights='imagenet')
       img_path = 'capyure.jpg'
       img = image.load_img(img_path, target_size=(224, 224))

       x = image.img_to_array(img)
       x = np.expand_dims(x, axis=0)
       x = preprocess_input(x)
       preds = model.predict(x)

       translator = Translator(to_lang='chinese')
       str =decode_predictions(preds, top=3)[0][0][1]
       translation = translator.translate(str.replace('_', ' '))
       return translation;

def change():
# 读取文件
pil_img = Image.open('capyure.jpg',)
# 读取cv2文件
#frame = Image.fromarray(cv2.cvtColor(img_path, cv2.COLOR_BGR2RGB))
# pil_img.show()
# 生成画笔
draw = ImageDraw.Draw(pil_img)
# 第一个参数是字体文件的路径，第二个是字体大小
font = ImageFont.truetype('msyh.ttc', 30, encoding='utf-8')
# 第一个参数是文字的起始坐标，第二个需要输出的文字，第三个是字体颜色，第四个是字体类型
draw.text((30,50), jieguo(), (0, 0, 0), font=font)


# PIL图片转cv2
img = cv2.cvtColor(np.array(pil_img), cv2.COLOR_RGB2BGR)
# 变得可以拉伸 winname 必须要一样，且设置可以拉伸在前面
cv2.namedWindow('capture_pic', cv2.WINDOW_NORMAL)
# 显示
cv2.imshow("capture_pic", img)
# 等待
cv2.waitKey(10)

if __name__=='__main__':