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