def get_cls():
cls_list = []
data_path = r'/data0/linjingkai/DataSet/AWA/testclasses.txt'
cls_file = io.open(data_path, 'r')
cls_name = ' '
while cls_name != '':
# 读取类别的名称并去掉换行符
cls_name = cls_file.readline().rstrip('\n')
# 确保没有加入无效的名称
if len(cls_name) != 0:
cls_list.append(cls_name)
print("当前运行类别为：", cls_list)
print(" ")
cls_file.close()
return cls_list
if __name__ == '__main__':
#pass in the username of the account you want to download
get_all_tweets("@AngelAlessandra")
import io
# Instantiates a client
client = vision.ImageAnnotatorClient()
for i in range(1, 25):
# The name of the image file to annotate
file_name = os.path.join(os.path.dirname(__file__), '%03d.jpg' % (i))
font = ImageFont.truetype("C:\Windows\Fonts\Arial.ttf", 30) #font
im = Image.open(file_name) #drawopen
# Loads the image into memory
with io.open(file_name, 'rb') as image_file:
content = image_file.read()
image = types.Image(content=content)
# Performs label detection on the image file
response = client.label_detection(image=image)
labels = response.label_annotations
print('image%dlabels:' % i)
j = 1
for label in labels:
j = j + 1
print(label.description)
print(label.score)
draw = ImageDraw.Draw(im)
annFile='%s/annotations/instances_%s.json'%(dataDir,dataType)
# In[3]:
# initialize COCO api for instance annotations
coco=COCO(annFile)
# get all images containing given categories, select one at random
catIds = coco.getCatIds(catNms=['person'])
imgIds = coco.getImgIds(catIds=catIds)
data=[]
for i in range(1,len(imgIds)):
print "Processing image ",i,"/",len(imgIds)
id_image=imgIds[i]
img = coco.loadImgs(id_image)[0]
print img['file_name']
shutil.copy('%s/images/%s/%s'%(dataDir,dataType,img['file_name']),'../person_image')
annIds = coco.getAnnIds(imgIds=id_image, catIds=catIds, iscrowd=None)
anns = coco.loadAnns(annIds)
bbox_list=[]
for j in range(0,len(anns)):
bbox_list.append(anns[j]['bbox'])
data.append({'file_name':img['file_name'],'image_id':id_image,'bbox':bbox_list})
import io, json
with io.open('bboxes.json', 'w', encoding='utf-8') as f:
f.write(unicode(json.dumps(data, ensure_ascii=False)))
def run(self):
os.chdir(self.coco_path)
#self.append_coco.emit("Current Path: "+self.coco_path)
path = "."
# ROI arrays
filenames = []
zips = []
dirs = []
# scanning
for d in os.walk(path):
for dir in d:
for r, d, f in os.walk(str(dir)):
for file in f:
if self.txt in file:
filenames.append(os.path.join(r, file))
elif ".zip" in file:
zips.append(os.path.join(r, file))
# Sorting
zips.sort()
filenames.sort()
# looping and decoding...
#self.append_coco.emit(zips)
self.progressBar_setMaximum.emit(len(filenames))
first_filenum = int(filenames[0].replace(
self.txt, "").replace("-", " ").split(" ")[-1])
has_zero = False
if first_filenum == 0:
has_zero = True
else:
has_zero = False
for j in range(len(zips)):
for i in range(len(filenames)):
self.progressBar.emit(i + 1)
# declare ROI file
roi = read_roi.read_roi_zip(zips[j])
roi_list = list(roi.values())
# ROI related file informations
filename = filenames[i].replace("./", "")
im = cv2.imread("./" + filename)
h, w, c = im.shape
size = os.path.getsize("./" + filename)
try:
f = open("via_region_data.json")
original = json.loads(f.read())
#self.append_coco.emit("Writing..."+str(zips[j]))
# Do something with the file
except FileNotFoundError:
#self.append_coco.emit("File not exisited, creating new file...")
original = {}
data = {
filename + str(size): {
"fileref": "",
"size": size,
"filename": filename,
"base64_img_data": "",
"file_attributes": {},
"regions": {},
}
}
# write json
for a in roi_list:
try:
filename2 = filename.replace(
self.txt, "").replace("-",
" ").split(" ")
roi_name = a["name"].replace(
"-", " ").split(" ")
roi_num = int(roi_name[0])
file_num = int(filename2[-1])
if has_zero:
roi_num -= 1
if file_num == roi_num:
#print(has_zero)
#print(int(filename2[-1]), " ", roi_num)
#print(a)
x_list = a["x"]
y_list = a["y"]
for l in range(len(x_list)):
if x_list[l] >= w:
x_list[l] = w
# self.append_coco.emit(x_list[j])
for k in range(len(y_list)):
if y_list[k] >= h:
y_list[k] = h
#self.append_coco.emit(y_list[k])
# parameters
x_list.append(a["x"][0])
y_list.append(a["y"][0])
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": x_list,
"all_points_y": y_list,
},
"region_attributes": {
"name": dirname(dir)
},
}
}
data[filename +
str(size)]["regions"].update(
regions)
original.update(data)
except KeyError:
#Line Exception
if a['type'] == "line":
x1 = a['x1']
x2 = a['x2']
y1 = a['y1']
y2 = a['y2']
width = a['width']
new_x_list = []
new_y_list = []
if (x1 - x2) == 0:
slope = 0
else:
slope = (y1 - y2) / (x1 - x2)
slope_a = (-1) / slope
midpoint = [(x1 + x2) / 2,
(y1 + y2) / 2]
#print("斜率: ",slope)
#print(slope_a)
x = Symbol('x')
weight = solve(
x**2 + (x * slope_a)**2 -
(width / 2)**2, x)
new_x_list.append(int(x1 -
(weight[1])))
new_x_list.append(int(x1 +
(weight[1])))
new_x_list.append(int(x2 -
(weight[0])))
new_x_list.append(int(x2 +
(weight[0])))
new_x_list.append(int(x1 -
(weight[1])))
new_y_list.append(
int(y1 - (weight[1] * slope_a)))
new_y_list.append(
int(y1 + (weight[1] * slope_a)))
new_y_list.append(
int(y2 - (weight[0] * slope_a)))
new_y_list.append(
int(y2 + (weight[0] * slope_a)))
new_y_list.append(
int(y1 - (weight[1] * slope_a)))
#print("x坐標", new_x_list)
#print("y坐標", new_y_list)
#fix index out of bound exception
for j in range(len(new_x_list)):
if (new_x_list[j] >= 2160):
new_x_list[j] = 2159
#print(new_x_list[j])
for k in range(len(new_y_list)):
if (new_y_list[k] >= 2160):
new_y_list[k] = 2159
#print(new_y_list[k])
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": new_x_list,
"all_points_y": new_y_list
},
"region_attributes": {
"name": dirname(dir)
}
}
}
data[filename +
str(size)]["regions"].update(
regions)
original.update(data)
elif a['type'] == "oval":
TWO_PI = np.pi * 2
angles = 128
angle_shift = TWO_PI / angles
phi = 0
center_x = (2 * (a['left']) +
a['width']) / 2
center_y = (2 * a['top'] +
a['height']) / 2
x_list = []
y_list = []
for i in range(angles):
phi += angle_shift
x_list.append(
int(center_x +
(a['width'] * np.cos(phi) /
2)))
y_list.append(
int(center_y +
(a['height'] *
np.sin(phi) / 2)))
print(x_list)
print(y_list)
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": x_list,
"all_points_y": y_list,
},
"region_attributes": {
"name": dirname(dir)
},
}
}
data[filename +
str(size)]["regions"].update(
regions)
original.update(data)
except IndexError:
self.append_coco.emit(
"[ERROR] Can't find any type specific files! (Maybe check the file type)"
)
with io.open("via_region_data.json",
"w",
encoding="utf-8") as f:
f.write(
json.dumps(original, ensure_ascii=False))
self.append_coco.emit("[INFO] Converted Successfully!")
def run_func(self, zips, filenames, json_name, folder):
count2 = 0
# Sorting
zips.sort()
filenames.sort()
# looping and decoding...
#self.append_coco.emit(zips)
for j in range(len(zips)):
for i in range(len(filenames)):
count2 += 1
# declare ROI file
roi = read_roi.read_roi_zip(self.coco_path + "/" + zips[j])
roi_list = list(roi.values())
# ROI related file informations
filename = filenames[i].replace("./", "")
im = cv2.imread(self.coco_path + '/' + filename)
h, w, c = im.shape
size = os.path.getsize(self.coco_path + '/' + filename)
try:
f = open(json_name)
original = json.loads(f.read())
f.close()
#self.append_coco.emit("Writing..."+str(zips[j]))
# Do something with the file
except ValueError: # includes simplejson.decoder.JSONDecodeError
print('Decoding JSON has failed')
except FileNotFoundError:
#self.append_coco.emit("File not exisited, creating new file...")
original = {}
data = {
filename + str(size): {
"fileref": "",
"size": size,
"filename": filename,
"base64_img_data": "",
"file_attributes": {},
"regions": {},
}
}
for a in roi_list:
try:
filename2 = filename.replace(self.txt, "").replace(
"-", " ").split(" ")
roi_name = a["name"].replace("-", " ").split(" ")
roi_num = int(roi_name[0])
file_num = int(filename2[-1])
first_filenum = int(filenames[0].replace(
self.txt, "").replace("-", " ").split(" ")[-1])
has_zero = False
if first_filenum == 0:
has_zero = True
else:
has_zero = False
if has_zero:
roi_num -= 1
if file_num == roi_num:
#print(has_zero)
#print(int(filename2[-1]), " ", roi_num)
#print(a)
x_list = a["x"]
y_list = a["y"]
for l in range(len(x_list)):
if x_list[l] >= w:
x_list[l] = w - 1
# self.append_coco.emit(x_list[j])
for k in range(len(y_list)):
if y_list[k] >= h:
y_list[k] = h - 1
#self.append_coco.emit(y_list[k])
# parameters
x_list.append(a["x"][0])
y_list.append(a["y"][0])
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": x_list,
"all_points_y": y_list,
},
"region_attributes": {
"name": dirname(folder)
},
}
}
data[filename +
str(size)]["regions"].update(regions)
original.update(data)
except KeyError:
#Line Exception
if a['type'] == "line":
x1 = a['x1']
x2 = a['x2']
y1 = a['y1']
y2 = a['y2']
width = a['width']
new_x_list = []
new_y_list = []
if (x1 - x2) == 0:
slope = 0
else:
slope = (y1 - y2) / (x1 - x2)
slope_a = (-1) / slope
midpoint = [(x1 + x2) / 2, (y1 + y2) / 2]
#print("斜率: ",slope)
#print(slope_a)
x = Symbol('x')
weight = solve(
x**2 + (x * slope_a)**2 - (width / 2)**2, x)
new_x_list.append(int(x1 - (weight[1])))
new_x_list.append(int(x1 + (weight[1])))
new_x_list.append(int(x2 - (weight[0])))
new_x_list.append(int(x2 + (weight[0])))
new_x_list.append(int(x1 - (weight[1])))
new_y_list.append(int(y1 - (weight[1] * slope_a)))
new_y_list.append(int(y1 + (weight[1] * slope_a)))
new_y_list.append(int(y2 - (weight[0] * slope_a)))
new_y_list.append(int(y2 + (weight[0] * slope_a)))
new_y_list.append(int(y1 - (weight[1] * slope_a)))
#print("x坐標", new_x_list)
#print("y坐標", new_y_list)
#fix index out of bound exception
for j in range(len(new_x_list)):
if (new_x_list[j] >= h):
new_x_list[j] = h - 1
#print(new_x_list[j])
for k in range(len(new_y_list)):
if (new_y_list[k] >= w):
new_y_list[k] = w - 1
#print(new_y_list[k])
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": new_x_list,
"all_points_y": new_y_list
},
"region_attributes": {
"name": dirname(folder)
}
}
}
data[filename +
str(size)]["regions"].update(regions)
original.update(data)
elif a['type'] == "oval":
TWO_PI = np.pi * 2
angles = 128
angle_shift = TWO_PI / angles
phi = 0
center_x = (2 * (a['left']) + a['width']) / 2
center_y = (2 * a['top'] + a['height']) / 2
x_list = []
y_list = []
for i in range(angles):
phi += angle_shift
x_list.append(
int(center_x +
(a['width'] * np.cos(phi) / 2)))
y_list.append(
int(center_y +
(a['height'] * np.sin(phi) / 2)))
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": x_list,
"all_points_y": y_list,
},
"region_attributes": {
"name": dirname(folder)
},
}
}
data[filename +
str(size)]["regions"].update(regions)
original.update(data)
except IndexError or FileNotFoundError:
self.append_coco.emit(
"[ERROR] Can't find any type specific files! (Maybe check the file type)"
)
with io.open(json_name, "w", encoding="utf-8") as f:
f.write(json.dumps(original, ensure_ascii=False))
f.close()
print("Converted File: ", json_name)
# initialize COCO api for instance annotations
coco = COCO(annFile)
# get all images containing given categories, select one at random
catIds = coco.getCatIds(catNms=['person'])
imgIds = coco.getImgIds(catIds=catIds)
data = []
for i in range(1, len(imgIds)):
print "Processing image ", i, "/", len(imgIds)
id_image = imgIds[i]
img = coco.loadImgs(id_image)[0]
print img['file_name']
shutil.copy('%s/images/%s/%s' % (dataDir, dataType, img['file_name']),
'../person_image')
annIds = coco.getAnnIds(imgIds=id_image, catIds=catIds, iscrowd=None)
anns = coco.loadAnns(annIds)
bbox_list = []
for j in range(0, len(anns)):
bbox_list.append(anns[j]['bbox'])
data.append({
'file_name': img['file_name'],
'image_id': id_image,
'bbox': bbox_list
})
import io, json
with io.open('bboxes.json', 'w', encoding='utf-8') as f:
f.write(unicode(json.dumps(data, ensure_ascii=False)))
def zip2coco(self):
self.get_coco()
os.chdir(self.coco_path)
path = "."
# ROI arrays
filenames = []
zips = []
dirs = []
# scanning
for d in os.walk(path):
for dir in d:
for r, d, f in os.walk(str(dir)):
for file in f:
if self.format_txt.toPlainText() in file:
filenames.append(os.path.join(r, file))
elif ".zip" in file:
zips.append(os.path.join(r, file))
# Sorting
zips.sort()
filenames.sort()
# looping and decoding...
print(zips)
for j in range(len(zips)):
for i in range(len(filenames)):
# declare ROI file
roi = read_roi.read_roi_zip(zips[j])
roi_list = list(roi.values())
# ROI related file informations
filename = filenames[i].replace(".\\",
"").replace(".\\", "")
im = cv2.imread(".\\" + filename)
h, w, c = im.shape
size = os.path.getsize(filename)
try:
f = open("via_region_data.json")
original = json.loads(f.read())
#print("Writing..."+str(zips[j]))
# Do something with the file
except FileNotFoundError:
print("File not exisited, creating new file...")
original = {}
data = {
filename + str(size): {
"fileref": "",
"size": size,
"filename": filename,
"base64_img_data": "",
"file_attributes": {},
"regions": {},
}
}
# write json
length = len(list(roi.values()))
self.progressBar.setMaximum(length)
for a in range(length):
filename2 = filename.replace(
self.format_txt.toPlainText(),
"").replace("-", " ").split(" ")
roi_name = roi_list[a]["name"].replace(
"-", " ").split(" ")
filenum = ""
if int(filename2[:1]) > 10 and int(
filename2[:1]) < 100:
filenum = "00" + str(int(filename2[:1]))
elif int(filename2[:1]) > 100 and int(
filename2[:1]) < 1000:
filenum = "0" + str(int(filename2[:1]))
elif int(filename2[:1]) > 1 and int(
filename2[:1]) < 10:
filenum = "000" + str(int(filename2[:1]))
elif int(filename2[:1]) > 1000 and int(
filename2[:1]) < 10000:
filenum = str(int(filename2[:1]))
if filenum == roi_name[0]:
print("roi_name: ", roi_name[0], "filename: ",
filenum)
x_list = roi_list[a]["x"]
y_list = roi_list[a]["y"]
for l in range(len(x_list)):
if x_list[l] >= w:
x_list[l] = w
# print(x_list[j])
for k in range(len(y_list)):
if y_list[k] >= h:
y_list[k] = h
# print(y_list[k])
# parameters
x_list.append(roi_list[a]["x"][0])
y_list.append(roi_list[a]["y"][0])
regions = {
str(a): {
"shape_attributes": {
"name": "polygon",
"all_points_x": x_list,
"all_points_y": y_list,
},
"region_attributes": {
"name":
dirname(dir).replace("-ROI", " ") +
"-" + str(j)
},
}
}
data[filename +
str(size)]["regions"].update(regions)
original.update(data)
with io.open("via_region_data.json",
"w",
encoding="utf-8") as f:
f.write(json.dumps(original, ensure_ascii=False))