193 lines
6.2 KiB
Python
193 lines
6.2 KiB
Python
from PIL import Image
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import numpy as np
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import cv2
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import base64
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import io,os
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import requests
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import time
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def test():
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image_path='test/P0017.png'
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image_array=cv2.imread(image_path)
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print(image_array.shape)
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image_encode=base64.b64encode(image_array).decode('utf-8')
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image_bytes=bytes(image_encode,encoding='utf-8')
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image_decode=np.frombuffer(base64.decodebytes(image_bytes),dtype=np.uint8)
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print(image_decode.shape)
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request_url='http://192.168.109.49:5000/'
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headers={'content-type':'application/json'}
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data={'image':image_encode}
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#response=requests.post(request_url,data=data,headers=headers)
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response=requests.post(request_url,"POST",files=data)
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print(response)
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#image=open(image_path,'rb').read()
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#image=Image.open(io.BytesIO(image))
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#image=image.resize((224,224))
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#image=np.asarray(image
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def test2():
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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api = 'http://192.168.16.45:8000/detector'
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img = cv2.imencode('.jpg', image_ori)[-1]
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#image_encode=base64.b64encode(image_ori).decode('utf-8')
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#img=bytes(image_encode,encoding='utf-8')
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#h,w,c=image_ori.shape
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files = {'file': img}
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files = {'file': img,'name':'P0017'
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}
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res = requests.request("POST", api, files=files).json()
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if res['msg'] == 'success':
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bboxes = res['data']['bboxes']
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print(bboxes)
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#bboxes = np.asarray(bboxes, dtype=np.int32)
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def get_file_content(filePath):
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with open(filePath, 'rb') as fp:
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return fp.read()
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def test3():
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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api = 'http://192.168.16.45:8000/detector'
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#img = cv2.imencode('.jpg', img_ori)[-1]
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input_ ={
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'img_data':'',
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'img_width':512,
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'img_height':512,
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'img_chs':3
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}
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with open(image_path,'rb') as f:
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input_['img_data']=base64.b64encode(f.read()).decode('utf-8')
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image_encode=base64.b64encode(image_ori).decode('utf-8')
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image_bytes=bytes(image_encode,encoding='utf-8')
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#input_['img_data']=image_bytes
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response=requests.post(api,json=input_).json()
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print(response['msg'],response['data']['bboxes'])
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###---客户端：读取图片:image_ori=cv2.imread(image_path)--->编码base64.b64encode(f.read()).decode('utf-8') ,(C,H,W)
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###---服务器端：字节化image_bytes=bytes(img_data,encoding='utf-8')-->解码img_data=np.frombuffer(base64.decodebytes(image_bytes),dtype=np.uint8)-->reshape:mg_data=img_data.reshape(h,w,3)
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def test4():
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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api = 'http://192.168.16.45:8000/detector'
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#img = cv2.imencode('.jpg', img_ori)[-1]
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h,w,c = image_ori.shape
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input_ ={
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'img_data':'',
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'img_width':h,
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'img_height':w,
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'img_chs':c
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}
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print('input:',input_)
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##decode('utf-8'),有没有好像都行。
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input_['img_data']=base64.b64encode(image_ori).decode('utf-8')
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response=requests.post(api,json=input_).json()
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print(response['msg'],response['data']['bboxes'])
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def decode_encode():
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##对文件b64编码，b64解码存储
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image_path='test/P0017.png'
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with open(image_path,'rb') as fp:
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encode_img = base64.b64encode(fp.read())
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with open('t2.png','wb') as f2:
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f2.write(base64.b64decode(encode_img))
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##输入时数组-->opencv编码jpg字节流-->存储图片文件
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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image_bytes = cv2.imencode(".png",image_ori)[1].tobytes()
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with open('bytes2image.png') as fp:
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fp.write(image_bytes)
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###字节流到数组用cv2.imdecode(np.frombuffer(image_bytes,np.uint8),1)
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with open(image_path,'rb') as fp:
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image_bytes2 = fp.read()
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image_array = cv2.imdecode(np.frombuffer(image_bytes2,np.uint8),1)
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##输入时数组-->opencv编码jpg字节流-->存储图片文件
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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image_bytes = cv2.imencode(".png",image_ori)[1].tobytes()
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with open('bytes2image.png') as fp:
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fp.write(image_bytes)
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##image_array--
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image_path='test/P0017.png'
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image_ori=cv2.imread(image_path)
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image_encode=base64.b64encode(image_ori).decode('utf-8')
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image_bytes=bytes(image_encode,encoding='utf-8')
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img_data=np.frombuffer(base64.decodebytes(image_bytes),dtype=np.uint8)
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def test5():
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import json
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##输入时数组-->opencv编码jpg字节流-->存储图片文件
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image_path='imgs/DJI_0445.JPG'
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image_dir = '/home/thsw2/WJ/data/THexit/val/images/'
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filelist = os.listdir(image_dir)
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time0 = time.time()
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for filename in filelist:
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image_path = os.path.join(image_dir,filename)
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image_ori=cv2.imread(image_path)
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image_ori = cv2.resize(image_ori, (0, 0), fx=0.25, fy=0.25, interpolation=cv2.INTER_NEAREST)
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image_pngcode = cv2.imencode(".jpg",image_ori)[-1]
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api = 'http://192.168.10.10:8000/detector'
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#api = 'http://47.98.157.120:9040/api/taskFile/submitUAVKHQuestion'
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#api = 'http://192.168.0.100:9040'
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h,w,c = image_ori.shape
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input_ ={
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'imgData':'',
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#'img_width':h,
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#'img_height':w,
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#'img_chs':c，
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'imgName':filename
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}
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#print('input:',input_ )
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t1 = time.time()
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image_code = str(base64.b64encode(image_pngcode))[2:-1]
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#print( image_code)
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input_['imgData']=image_code
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t2 = time.time()
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response=requests.post(api,json=input_).json()
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t3 = time.time()
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print('bs encodetime:%.5f request time:%.5f \n'%(t2-t1,t3-t2))
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t1_bytes = bytes(image_code,encoding='utf-8')
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t2_bs64decode = base64.b64decode(t1_bytes)
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img_data = cv2.imdecode(np.frombuffer(base64.b64decode( bytes(image_code,encoding='utf-8')),dtype=np.uint8),1)
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#print(response['code'],response['data']['bboxes'])
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print('Return:',response['data']['bboxes'],' img data shape:',img_data.shape)
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time2 = time.time()
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print('average time:',(time2-time0)/len(filelist))
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if __name__=='__main__':
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test5()
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