196 lines
7.1 KiB
Python
196 lines
7.1 KiB
Python
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import os
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import shutil
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import cv2
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import numpy as np
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def allFilePath(rootPath,allFIleList):
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fileList = os.listdir(rootPath)
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for temp in fileList:
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if os.path.isfile(os.path.join(rootPath,temp)):
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if temp.endswith(".jpg"):
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allFIleList.append(os.path.join(rootPath,temp))
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else:
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allFilePath(os.path.join(rootPath,temp),allFIleList)
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def order_points(pts):
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# initialzie a list of coordinates that will be ordered
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# such that the first entry in the list is the top-left,
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# the second entry is the top-right, the third is the
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# bottom-right, and the fourth is the bottom-left
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pts=pts[:4,:]
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rect = np.zeros((5, 2), dtype = "float32")
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# the top-left point will have the smallest sum, whereas
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# the bottom-right point will have the largest sum
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s = pts.sum(axis = 1)
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rect[0] = pts[np.argmin(s)]
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rect[2] = pts[np.argmax(s)]
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# now, compute the difference between the points, the
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# top-right point will have the smallest difference,
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# whereas the bottom-left will have the largest difference
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diff = np.diff(pts, axis = 1)
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rect[1] = pts[np.argmin(diff)]
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rect[3] = pts[np.argmax(diff)]
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# return the ordered coordinates
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return rect
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def get_partical_ccpd():
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ccpd_dir = r"/mnt/Gpan/BaiduNetdiskDownload/CCPD1/CCPD2020/ccpd_green"
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save_Path = r"ccpd/green_plate"
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folder_list = os.listdir(ccpd_dir)
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for folder_name in folder_list:
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count=0
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folder_path = os.path.join(ccpd_dir,folder_name)
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if os.path.isfile(folder_path):
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continue
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if folder_name == "ccpd_fn":
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continue
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name_list = os.listdir(folder_path)
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save_folder=save_Path
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if not os.path.exists(save_folder):
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os.mkdir(save_folder)
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for name in name_list:
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file_path = os.path.join(folder_path,name)
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count+=1
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if count>1000:
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break
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new_file_path =os.path.join(save_folder,name)
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shutil.move(file_path,new_file_path)
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print(count,new_file_path)
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def get_rect_and_landmarks(img_path):
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file_name = img_path.split("/")[-1].split("-")
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landmarks_np =np.zeros((5,2))
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rect = file_name[2].split("_")
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landmarks=file_name[3].split("_")
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rect_str = "&".join(rect)
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landmarks_str= "&".join(landmarks)
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rect= rect_str.split("&")
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landmarks=landmarks_str.split("&")
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rect=[int(x) for x in rect]
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landmarks=[int(x) for x in landmarks]
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for i in range(4):
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landmarks_np[i][0]=landmarks[2*i]
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landmarks_np[i][1]=landmarks[2*i+1]
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# middle_landmark_w =int((landmarks[4]+landmarks[6])/2)
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# middle_landmark_h =int((landmarks[5]+landmarks[7])/2)
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# landmarks.append(middle_landmark_w)
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# landmarks.append(middle_landmark_h)
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landmarks_np_new=order_points(landmarks_np)
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# landmarks_np_new[4]=np.array([middle_landmark_w,middle_landmark_h])
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return rect,landmarks,landmarks_np_new
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def x1x2y1y2_yolo(rect,landmarks,img):
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h,w,c =img.shape
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rect[0] = max(0, rect[0])
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rect[1] = max(0, rect[1])
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rect[2] = min(w - 1, rect[2]-rect[0])
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rect[3] = min(h - 1, rect[3]-rect[1])
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annotation = np.zeros((1, 14))
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annotation[0, 0] = (rect[0] + rect[2] / 2) / w # cx
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annotation[0, 1] = (rect[1] + rect[3] / 2) / h # cy
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annotation[0, 2] = rect[2] / w # w
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annotation[0, 3] = rect[3] / h # h
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annotation[0, 4] = landmarks[0] / w # l0_x
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annotation[0, 5] = landmarks[1] / h # l0_y
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annotation[0, 6] = landmarks[2] / w # l1_x
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annotation[0, 7] = landmarks[3] / h # l1_y
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annotation[0, 8] = landmarks[4] / w # l2_x
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annotation[0, 9] = landmarks[5] / h # l2_y
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annotation[0, 10] = landmarks[6] / w # l3_x
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annotation[0, 11] = landmarks[7] / h # l3_y
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# annotation[0, 12] = landmarks[8] / w # l4_x
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# annotation[0, 13] = landmarks[9] / h # l4_y
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return annotation
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def xywh2yolo(rect,landmarks_sort,img):
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h,w,c =img.shape
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rect[0] = max(0, rect[0])
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rect[1] = max(0, rect[1])
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rect[2] = min(w - 1, rect[2]-rect[0])
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rect[3] = min(h - 1, rect[3]-rect[1])
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annotation = np.zeros((1, 12))
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annotation[0, 0] = (rect[0] + rect[2] / 2) / w # cx
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annotation[0, 1] = (rect[1] + rect[3] / 2) / h # cy
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annotation[0, 2] = rect[2] / w # w
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annotation[0, 3] = rect[3] / h # h
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annotation[0, 4] = landmarks_sort[0][0] / w # l0_x
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annotation[0, 5] = landmarks_sort[0][1] / h # l0_y
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annotation[0, 6] = landmarks_sort[1][0] / w # l1_x
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annotation[0, 7] = landmarks_sort[1][1] / h # l1_y
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annotation[0, 8] = landmarks_sort[2][0] / w # l2_x
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annotation[0, 9] = landmarks_sort[2][1] / h # l2_y
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annotation[0, 10] = landmarks_sort[3][0] / w # l3_x
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annotation[0, 11] = landmarks_sort[3][1] / h # l3_y
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# annotation[0, 12] = landmarks_sort[4][0] / w # l4_x
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# annotation[0, 13] = landmarks_sort[4][1] / h # l4_y
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return annotation
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def yolo2x1y1x2y2(annotation,img):
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h,w,c = img.shape
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rect= annotation[:,0:4].squeeze().tolist()
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landmarks=annotation[:,4:].squeeze().tolist()
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rect_w = w*rect[2]
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rect_h =h*rect[3]
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rect_x =int(rect[0]*w-rect_w/2)
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rect_y = int(rect[1]*h-rect_h/2)
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new_rect=[rect_x,rect_y,rect_x+rect_w,rect_y+rect_h]
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for i in range(5):
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landmarks[2*i]=landmarks[2*i]*w
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landmarks[2*i+1]=landmarks[2*i+1]*h
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return new_rect,landmarks
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def write_lable(file_path):
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pass
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if __name__ == '__main__':
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file_root = r"ccpd"
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file_list=[]
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count=0
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allFilePath(file_root,file_list)
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for img_path in file_list:
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count+=1
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# img_path = r"ccpd_yolo_test/02-90_85-173&466_452&541-452&553_176&556_178&463_454&460-0_0_6_26_15_26_32-68-53.jpg"
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text_path= img_path.replace(".jpg",".txt")
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img =cv2.imread(img_path)
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rect,landmarks,landmarks_sort=get_rect_and_landmarks(img_path)
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# annotation=x1x2y1y2_yolo(rect,landmarks,img)
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annotation=xywh2yolo(rect,landmarks_sort,img)
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str_label = "0 "
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for i in range(len(annotation[0])):
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str_label = str_label + " " + str(annotation[0][i])
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str_label = str_label.replace('[', '').replace(']', '')
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str_label = str_label.replace(',', '') + '\n'
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with open(text_path,"w") as f:
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f.write(str_label)
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print(count,img_path)
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# get_partical_ccpd()
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# file_root = r"ccpd/green_plate"
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# file_list=[]
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# allFilePath(file_root,file_list)
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# count=0
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# for img_path in file_list:
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# img_name = img_path.split(os.sep)[-1]
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# if not "&" in img_name:
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# count+=1
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# os.remove(img_path)
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# print(count,img_path)
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# new_rect,new_landmarks=yolo2x1y1x2y2(annotation,img)
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# rect= [int(x) for x in new_rect]
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# cv2.rectangle(img,(rect[0],rect[1]),(rect[2],rect[3]),(255,0,0),2)
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# colors=[(0,255,0),(0,255,255),(255,255,0),(255,255,255),(255,0,255)] #绿 黄 青 白
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# for i in range(5):
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# cv2.circle(img,(landmarks[2*i],landmarks[2*i+1]),2,colors[i],2)
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# cv2.imwrite("1.jpg",img)
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# print(rect,landmarks)
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# get_partical_ccpd()
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