def get_cropped(name, new=False):
# If a new subject, call the Cloud Vision API
if new:
crop_image(name)
polygon = None
# Load bounding box
with open(name + '.p', 'rb') as f:
polygon = pickle.load(f)
polygon = np.array([[p.x, p.y] for p in polygon])
# Load image and darken the image
image = io.imread(name + '.jpg')
image = exposure.adjust_gamma(image, gamma=1.5, gain=1)
x = image.shape[1]
y = image.shape[0]
# Draw a rectangle to crop the image
rect = mpatches.Rectangle((polygon[0][0] * x, polygon[0][1] * y),
polygon[1][0] * x - polygon[0][0] * x, polygon[2][1] * y -
polygon[0][1] * y, linewidth=1, edgecolor='r', facecolor='none')
bbox = rect.get_bbox()
cropped = image[int(bbox.y0):int(bbox.y1), int(bbox.x0):int(bbox.x1)]
return cropped
def run_c3(image, training_path):
"""reads temperature for a single image"""
#FOR CAMERA 3 ONLY
info = check(image)
valid = info[0]
if valid != None:
return valid
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [2124] #pictype 3 heights
valid_widths = [3776] #pictype 3 widths
if width not in valid_widths or height not in valid_heights:
return "Temp is: {0}".format(-9999)
if not os.path.exists(os.getcwd() +
'/temp/'): #if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
crop.crop_image(image, "temp/digits.jpg", 435, 0, 70, 30) #crops digits
temperature = ocr_contour.recognize('temp/digits.jpg',
training_path) #recognize digit
os.remove(os.getcwd() + '/temp/digits.jpg') #clean up temp dir
temp = ''
for i in temperature:
temp += i
try:
return int(temp)
except:
return "Temp is: {0}".format(-9999)
def run_c4(image, training_path):
"""reads temperature for a single image"""
#FOR CAMERA 4 ONLY
info = check(image)
valid = info[0]
if valid != None:
return valid
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [1512] #pictype 4 heights
valid_widths = [2688] #pictype 4 widths
if width not in valid_widths or height not in valid_heights:
return int(-9999)
if not os.path.exists(os.getcwd()+'/temp/'): #if temp folder doesnt exis, create one
os.makedirs(os.getcwd()+'/temp/')
crop.crop_image(image, "temp/digits.jpg", 825, 1445, 145, 70)
temperature = ocr_contour.recognize('temp/digits.jpg', training_path, True) #recognize digits
# im = cv2.imread('temp/digits.jpg') ##debugging
# cv2.imshow('img', im) ##debugging
# cv2.waitKey(0) ##debugging
final = sorted(temperature, key = lambda x: x[1][0]) #sort from left to right
os.remove(os.getcwd()+'/temp/digits.jpg') #clean up temp dir
temp = ''
for digit in final:
temp += digit[0]
try:
return int(temp)
except:
return int(-9999)
def sortByEmotionMenu(self): crop.crop_image(self.pathImages) emotion_sort.sort_e(self.pathCroppedImages) PhotoGallery.gallery(self.pathSortedImages, 250, 200) self.updateGallery2() self.raise_frame(self.f3) videorender.render(self.pathSortedImages)
def run_c2(image, training_path):
'''Reads temperature values from HC500/HC600 Hyperfire cameras
Writes any found mismatches on task3/mismatches/ in a .txt file
w/ a randomly generated filename'''
info = check(image)
valid = check(image)[0]
width, height = info[1][0], info[1][1]
valid_widths = [1920, 2048] # pictype 2 heights
valid_heights = [1080, 1536] # pictype 2 widths
if width not in valid_widths or height not in valid_heights:
return int(-9999)
if not os.path.exists(os.getcwd() + '/temp/'): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
if height == valid_heights[0] and width == valid_widths[0]: #1920x2040
crop.crop_image(image, "temp/digits.jpg", 1710, 0, 115, 30) # crops digits
elif height == valid_heights[1] and width == valid_widths[1]: #2048x1536
crop.crop_image(image, "temp/digits.jpg", 1850, 0, 105, 30)
temperature = ocr_contour.recognize(os.getcwd() + '/temp/digits.jpg', training_path) # recognize right digit
# os.remove(os.getcwd()+'/temp/digits.jpg') #clean up temp dir
ocr_temp = ''
for digit in temperature:
ocr_temp += digit
if valid != None:
exif_temp = int(valid)
ocr_temp = int(ocr_temp)
try:
if ocr_temp != exif_temp:
if not os.path.exists(os.getcwd() + '/mismatches/'): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/mismatches/')
f = open("mismatches/{0}.jpg".format(id_generator()), "w")
f.write("exif temp: {0}, ocr temp: {1}, filename: {2}".format(exif_temp,ocr_temp,image))
return int(ocr_temp)
except:
return int(-9999)
def sortByColorMenu(self): crop.crop_image(self.pathImages) colorfulness.sort_c(self.pathCroppedImages) PhotoGallery.gallery(self.pathSortedImages, 250, 200) self.updateGallery2() self.raise_frame(self.f3) videorender.render(self.pathSortedImages)
def run_c1(image, training_path):
'''reads temperature of images in a directory. CAMERA 1 ONLY'''
info = check(image)
valid = info[0]
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [2448] #pictype 3 heights
valid_widths = [3264] #pictype 3 widths
if width not in valid_widths or height not in valid_heights:
return int(-9999)
if valid != None:
return valid
if not os.path.exists(os.getcwd() + '/temp/'): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
crop.crop_image(image,'temp/digits.jpg', 790, 2355, 375, 70)
crop.invert(os.getcwd() + '/temp/digits.jpg')
info = ocr_contour.recognize(os.getcwd() + '/temp/digits.jpg', training_path, True)
temp = []
for item in info:
if item[0] == '45':
x1,y1 = item[1][0], item[1][1]
for item in info:
if item[1][0] < x1:
temp.append((item[0], item[1][0]))
final = sorted(temp, key = lambda x: x[1])
temperature = ''
for i in final:
temperature += i[0]
try:
return int(temperature)
except:
return int(-9999)
def run_c3(image, training_path):
"""reads temperature for a single image"""
#FOR CAMERA 3 ONLY
info = check(image)
valid = info[0]
if valid != None:
return valid
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [2124] #pictype 3 heights
valid_widths = [3776] #pictype 3 widths
if width not in valid_widths or height not in valid_heights:
return int(-9999)
if not os.path.exists(os.getcwd()+'/temp/'): #if temp folder doesnt exis, create one
os.makedirs(os.getcwd()+'/temp/')
crop.crop_image(image, "temp/digits.jpg", 435, 0, 70, 30) #crops digits
temperature = ocr_contour.recognize('temp/digits.jpg', training_path) #recognize digit
os.remove(os.getcwd()+'/temp/digits.jpg') #clean up temp dir
temp = ''
for i in temperature:
temp +=i
try:
return int(temp)
except:
return int(-9999)
def run_c1(image, training_path):
'''reads temperature of images in a directory. CAMERA 1 ONLY'''
info = check(image)
valid = info[0]
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [2448] #pictype 3 heights
valid_widths = [3264] #pictype 3 widths
if width not in valid_widths or height not in valid_heights:
return "Temp is: {0}".format(-9999)
if valid != None:
return valid
if not os.path.exists(os.getcwd() +
'/temp/'): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
crop.crop_image(image, 'temp/digits.jpg', 790, 2355, 375, 70)
crop.invert(os.getcwd() + '/temp/digits.jpg')
info = ocr_contour.recognize(os.getcwd() + '/temp/digits.jpg',
training_path, True)
temp = []
for item in info:
if item[0] == '45':
x1, y1 = item[1][0], item[1][1]
for item in info:
if item[1][0] < x1:
temp.append((item[0], item[1][0]))
final = sorted(temp, key=lambda x: x[1])
temperature = ''
for i in final:
temperature += i[0]
try:
return int(temperature)
except:
return "Temp is: {0}".format(-9999)
def run_c4(image, training_path):
"""reads temperature for a single image"""
#FOR CAMERA 4 ONLY
info = check(image)
valid = info[0]
if valid != None:
return valid
width, height = info[1][0], info[1][1]
exif_json = info[2]
valid_heights = [1512] #pictype 4 heights
valid_widths = [2688] #pictype 4 widths
if width not in valid_widths or height not in valid_heights:
return "Temp is: {0}".format(-9999)
if not os.path.exists(os.getcwd() +
'/temp/'): #if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
crop.crop_image(image, "temp/digits.jpg", 825, 1445, 145, 70)
temperature = ocr_contour.recognize('temp/digits.jpg', training_path,
True) #recognize digits
# im = cv2.imread('temp/digits.jpg') ##debugging
# cv2.imshow('img', im) ##debugging
# cv2.waitKey(0) ##debugging
final = sorted(temperature,
key=lambda x: x[1][0]) #sort from left to right
os.remove(os.getcwd() + '/temp/digits.jpg') #clean up temp dir
temp = ''
for digit in final:
temp += digit[0]
try:
return int(temp)
except:
return "Temp is: {0}".format(-9999)
def main(args):
if not os.path.exists(cropped_folder):
os.mkdir(cropped_folder)
if not os.path.exists(saliency_folder):
os.mkdir(saliency_folder)
if args.rgb_folder:
rgb_pths = os.listdir(args.rgb_folder)
for rgb_pth in rgb_pths:
saliency(args.rgb_folder, rgb_pth)
crop_image(args.rgb_folder, rgb_pth)
#print(os.path.join(args.rgb_folder,rgb_pth))
else:
saliency(None, args.rgb)
crop_image(None, args.rgb)
def prepare_data(user_id: int):
data = dict()
source = user_videos[user_id]['source']
target = user_videos[user_id]['target']
audio_clip = AudioFileClip(target)
data['audio'] = audio_clip
if source.endswith('.jpg'):
crop_image(source)
else:
# pass
crop_video(source)
try:
source_reader = imageio.get_reader('crop_' + source)
except FileNotFoundError:
print("Didn't find cropped video")
source_reader = imageio.get_reader(source)
if source.endswith('.jpg'):
data['source_media'] = resize(next(iter(source_reader)), (256, 256))[..., :3]
data['photo'] = True
else:
data['source_media'] = read_video(source_reader)
data['photo'] = False
crop_video(target)
try:
target_reader = imageio.get_reader('crop_' + target)
except FileNotFoundError:
print("Didn't find cropped video")
target_reader = imageio.get_reader(target)
fps = target_reader.get_meta_data()['fps']
data['fps'] = fps
data['target_media'] = read_video(target_reader)
generator, kp_detector = load_checkpoints(config_path=CONFIG,
checkpoint_path=CHECKPOINT,
cpu=CPU)
data['generator'] = generator
data['kp_detector'] = kp_detector
return data
def run_c2(image, training_path):
'''Reads temperature values from HC500/HC600 Hyperfire cameras
Writes any found mismatches on task3/mismatches/ in a .txt file
w/ a randomly generated filename'''
info = check(image)
valid = check(image)[0]
width, height = info[1][0], info[1][1]
valid_widths = [1920, 2048] # pictype 2 heights
valid_heights = [1080, 1536] # pictype 2 widths
if width not in valid_widths or height not in valid_heights:
return "Temp is: {0}".format(-9999)
if not os.path.exists(os.getcwd() +
'/temp/'): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/temp/')
if height == valid_heights[0] and width == valid_widths[0]: #1920x2040
crop.crop_image(image, "temp/digits.jpg", 1710, 0, 115,
30) # crops digits
elif height == valid_heights[1] and width == valid_widths[1]: #2048x1536
crop.crop_image(image, "temp/digits.jpg", 1850, 0, 105, 30)
temperature = ocr_contour.recognize(os.getcwd() + '/temp/digits.jpg',
training_path) # recognize right digit
# os.remove(os.getcwd()+'/temp/digits.jpg') #clean up temp dir
ocr_temp = ''
for digit in temperature:
ocr_temp += digit
if valid != None:
exif_temp = int(valid)
ocr_temp = int(ocr_temp)
try:
if ocr_temp != exif_temp:
if not os.path.exists(os.getcwd() + '/mismatches/'
): # if temp folder doesnt exis, create one
os.makedirs(os.getcwd() + '/mismatches/')
f = open("mismatches/{0}.jpg".format(id_generator()), "w")
f.write("exif temp: {0}, ocr temp: {1}, filename: {2}".format(
exif_temp, ocr_temp, image))
return int(ocr_temp)
except:
return "Temp is: {0}".format(-9999)
def main(args):
if not os.path.exists(cropped_folder):
os.mkdir(cropped_folder)
if not os.path.exists(saliency_folder):
os.mkdir(saliency_folder)
if args.rgb_folder:
rgb_pths = os.listdir(args.rgb_folder)
count = 1
for rgb_pth in rgb_pths:
print("IMAGE:", end=' ')
print(count)
count = count + 1
saliency(args.rgb_folder, rgb_pth)
crop_image(args.rgb_folder, rgb_pth)
print()
#print(os.path.join(args.rgb_folder,rgb_pth))
else:
saliency(None, args.rgb)
crop_image(None, args.rgb)
def ajax_save_images(request):
if request.user.is_authenticated():
img_crop_dict = copy.deepcopy(eval(request.POST['crop_dictionary']))
for file_key, file_val in request.FILES.items():
extra_details = ImageInfo.objects.filter(user=request.user,
type='Profile')
if len(extra_details) <= 0:
file_val.name = str(
request.user.id
) + '_' + file_key + '.' + file_val.name.split('.')[-1]
extra_details = ImageInfo(user=request.user,
type='Profile',
photo=file_val)
extra_details.save()
else:
extra_details = extra_details[0]
counter = extra_details.photo.name.split('.')[0].split('_')[-1]
try:
counter = int(counter) + 1
except Exception:
counter = 0
old_pic_name = extra_details.photo.name
temp_list = old_pic_name.split('c_')[-1].split('.')[0].split(
'_')
tmp_var = temp_list[0]
new_pic_name = tmp_var + '_' + str(
counter) + '.' + old_pic_name.split('.')[-1]
file_val.name = new_pic_name
extra_details.photo = file_val
extra_details.save()
if img_crop_dict.has_key('upfile'):
crop_dict = img_crop_dict['upfile']
crop_dict['image_name'] = extra_details.photo.name
path = crop_image(crop_dict)
extra_details.photo.name = path
extra_details.save()
path_image = settings.MEDIA_URL + path
return HttpResponse(path_image)
else:
return HttpResponse('error in uploading file')
def grade_all(warped):
total_grade = 0
try:
gray = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
except:
thresh = cv2.threshold(warped, 0, 255,
cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
if debug:
show_image(
thresh
) #------------------------------------------------------------------------------------------
first_part, second_part, third_part = crop_image(thresh)
total_grade = grade_1(first_part) + grade_2(second_part) + grade_3(
third_part)
return total_grade
def ajax_save_images( request ):
if request.user.is_authenticated():
img_crop_dict = copy.deepcopy( eval( request.POST['crop_dictionary'] ) )
for file_key, file_val in request.FILES.items():
extra_details = ImageInfo.objects.filter( user = request.user, type = 'Profile' )
if len( extra_details ) <= 0:
file_val.name = str( request.user.id ) + '_' + file_key + '.' + file_val.name.split( '.' )[-1]
extra_details = ImageInfo( user = request.user, type = 'Profile', photo = file_val )
extra_details.save()
else:
extra_details = extra_details[0]
counter = extra_details.photo.name.split( '.' )[0].split( '_' )[-1]
try:
counter = int( counter ) + 1
except Exception:
counter = 0
old_pic_name = extra_details.photo.name
temp_list = old_pic_name.split( 'c_' )[-1].split( '.' )[0].split( '_' )
tmp_var = temp_list[0]
new_pic_name = tmp_var + '_' + str( counter ) + '.' + old_pic_name.split( '.' )[-1]
file_val.name = new_pic_name
extra_details.photo = file_val
extra_details.save()
if img_crop_dict.has_key( 'upfile'):
crop_dict = img_crop_dict['upfile']
crop_dict['image_name'] = extra_details.photo.name
path = crop_image( crop_dict )
extra_details.photo.name = path
extra_details.save()
path_image = settings.MEDIA_URL + path
return HttpResponse( path_image )
else:
return HttpResponse( 'error in uploading file' )
def cropped_puzzle(self): # 원본 사진을 받아와서 오리기
self.cropped_puzzle = crop.crop_image(self.cellSize)
time.sleep(1)
continue
if int(data) == 1:
print("GOt 1")
elif int(data) == 2:
print("GOt 2")
elif int(data) == 3:
print("GOt 3")
elif int(data) == 4:
print("GOt 4")
else:
continue
print(data)
image_path = "images/buttonrpi-yellow.jpg"
end_result = {'description': ''}
# camera.start_preview(alpha=200)
camera.capture(image_path)
# camera.stop_preview()
crop_image(image_path, int(data))
image_analyze(end_result, image_path)
print(end_result)
if end_result["description"]:
engine.say(end_result["description"])
engine.runAndWait()
else:
engine.say('Nothing to describe in the image.')
socker.close()
parser.add_argument("--cpu",
dest="cpu",
action="store_true",
help="cpu mode.")
parser.add_argument("--from_image", dest="from_image", action="store_true")
parser.set_defaults(relative=False)
parser.set_defaults(adapt_scale=False)
parser.set_defaults(from_image=False)
opt = parser.parse_args()
# opt.cpu = True
if opt.from_image:
crop.crop_image(opt.source_image)
else:
crop.crop_video(opt.source_image)
crop.crop_video(opt.driving_video)
try:
source_reader = imageio.get_reader('crop_' + opt.source_image)
except Exception as e:
print(e)
source_reader = imageio.get_reader(opt.source_image)
if opt.from_image:
source_photo = resize(next(iter(source_reader)), (256, 256))[..., :3]
else:
source_video = read_video(source_reader)
def zoom_image(image, percentage_height, percentage_width):
height, width = image.shape[:2]
newHeight = int(height + percentage_height/100 * height)
newWidth = int(width + percentage_width/100 * width)
zoomed = cv2.resize(img, dsize=(newHeight, newWidth))
return crop_image(zoomed, height, width)
print("GOt 2")
elif int(data) == 3:
print("GOt 3")
elif int(data) == 4:
print("GOt 4")
else:
continue
print(data)
image_path = sys.argv[1]
if not os.path.exists(image_path):
sys.exit()
end_result = {'description': ''}
# camera.start_preview(alpha=200)
#camera.capture(image_path)
# camera.stop_preview()
filename, file_extension = os.path.splitext(image_path)
cropped_path = 'images/cropped' + str(file_extension)
crop_image(image_path, int(data), True)
image_analyze(end_result, cropped_path)
print(end_result)
if end_result["description"]:
engine.say(end_result["description"])
engine.runAndWait()
else:
engine.say('Nothing to describe in the image.')
socket.close()
text = loader.preprocess(text)
model = state.load_best_model()
res = model.predict(np.array([text]))
le_path = os.path.join(args['text_model'], 'label_encoder.pkl')
le = loader.load_label_encoder(le_path)
print("text label:")
print(le.inverse_transform(res))
# image
state = TrainingState(args['image_model'])
loader = DataLoader('image')
images = []
for i in crop_image(captcha):
images.append(loader.preprocess(i))
model = state.load_best_model()
res = model.predict(np.array(images))
le_path = os.path.join(args['image_model'], 'label_encoder.pkl')
le = loader.load_label_encoder(le_path)
print("image labels:")
print(le.inverse_transform(res))
cv2.imshow('press any key to escape', captcha)
cv2.waitKey(0)
