def label_image_volc(self):
# download images
try:
urllib.request.urlretrieve(self.image_url, IMAGE_LOCAL)
except (URLError, HTTPError):
raise RuntimeError("Failed to download '{}'".format(self.image_url))
# Load TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(MODEL_PATH)
interpreter.allocate_tensors()
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()
# NxHxWxC, H:1, W:2
height = input_details[0]['shape'][1]
width = input_details[0]['shape'][2]
img, input_data = self.load_images(IMAGE_LOCAL, height, width)
# crop image for best display
sc = smartcrop.SmartCrop()
crop_r = sc.crop(img, 160, 90)
crop_r['top_crop'].pop('score')
crop_s = sc.crop(img, 100, 100)
crop_s['top_crop'].pop('score')
input_data = (np.float32(input_data) - INPUT_MEAN) / INPUT_STD
interpreter.set_tensor(input_details[0]['index'], input_data)
interpreter.invoke()
output_data = interpreter.get_tensor(output_details[0]['index'])
results = np.squeeze(output_data)
results = self.format_results_volc(results, LABEL_PATH, crop_r['top_crop'], crop_s['top_crop'])
return results
async def get_smartcrop(request, width, height, url):
async with httpx.AsyncClient(timeout=30) as client:
response = await client.get(url)
try:
response.raise_for_status()
except (httpx.RequestError, httpx.HTTPStatusError):
return HttpResponseBadRequest()
image_io = BytesIO()
async for chunk in response.aiter_bytes():
image_io.write(chunk)
image_io.seek(0)
sm = smartcrop.SmartCrop()
image = Image.open(image_io)
_width, _height = int(width), int(height)
result = sm.crop(
image=image,
width=100,
height=int(_height / _width * 100),
prescale=True,
)['top_crop']
x, y = result['x'], result['y']
w, h = result['width'], result['height']
crop = image.crop((x, y, x + w, y + h)).resize((_width, _height))
crop_io = BytesIO()
crop.save(crop_io, format='png')
crop_io.seek(0)
return HttpResponse(crop_io.read(), content_type='image/png')
def create_thumb_py(self, mode=None, pth=None):
""" Create the thumbnail using SmartCrop.py """
if pth is None:
raise ValueError("path can't be None")
# Load smartcrop and set options
sc = smartcrop.SmartCrop()
# Get desired dimensions
nwidth, nheight = self.resize_dims(mode)
factor = nwidth / 100.0
crop_width = 100 if settings.fast else nwidth
crop_height = int(nheight / factor) if settings.fast else nheight
logging.info("[%s] SmartCrop.py new dimensions: %ix%i" %
(self.name, nwidth, nheight))
# Fix image mode if necessary
img = self.original_image.copy()
if not img.mode in ["RGB", "RGBA"]:
newimg = Image.new("RGB", img.size)
newimg.paste(img)
img = newimg
# Calculate the optimal crop size
logging.info("[%s] SmartCrop.py computing optimal crop size." %
self.name)
ret = sc.crop(img, crop_width, crop_height)
box = (
ret["top_crop"]["x"],
ret["top_crop"]["y"],
ret["top_crop"]["width"] + ret["top_crop"]["x"],
ret["top_crop"]["height"] + ret["top_crop"]["y"],
)
# Do the actual crop
nimg = self.original_image.crop(box)
nimg.load()
nimg.thumbnail((nwidth, nheight), Image.ANTIALIAS)
# Create the filename and save the thumbnail
logging.info("[%s] Saving SmartCrop.py thumbnail." % self.name)
if settings.output_format == "jpg":
nimg.save(
pth,
optimize=settings.jpeg_optimize,
progressive=settings.jpeg_progressive,
quality=settings.jpeg_quality,
)
else:
nimg.save(pth)
return pth
def create(self, validated_data):
imgpath = MEDIA_ROOT + "/uploads/" + str(validated_data["image"])
width = validated_data["width"]
height = validated_data["height"]
smartcropimage = SmartcropImage.objects.create(**validated_data)
image = ImagePIL.open(imgpath)
sc = smartcrop.SmartCrop()
result = sc.crop(image, width, height)
smartcropimage.result = result
return smartcropimage
def GenerateImage():
sc = smartcrop.SmartCrop()
masks = list(os.scandir("./masks"))
images = list(os.scandir("./images"))
images = random.sample(images, len(masks))
result = Image.new("RGB", (1500, 500), (21, 32, 43))
for [mask, image] in zip(masks, images):
mask = Image.open(mask.path).convert('RGB')
maskL = mask.convert("L")
mask = numpy.array(mask)
x, y, width, height = bbox(mask)
src = Image.open(image.path).convert('RGB')
bounds = sc.crop(src, width, height)["top_crop"]
src = src.resize(
(width, height),
resample=Image.LANCZOS,
box=(bounds["x"], bounds["y"], bounds["width"] + bounds["x"],
bounds["height"] + bounds["y"]))
src = pad(src, x, y)
src = numpy.array(src)
dst = mask / 255 * src
dst = Image.fromarray(dst.astype(numpy.uint8))
result.paste(dst, (0, 0), maskL)
timestr = time.strftime("%Y%m%d-%H%M%S")
filename = f"./results/{timestr}_result.png"
result.save(filename)
api = twitter.Api(
consumer_key=os.environ.get('TWITTER_API_KEY'),
consumer_secret=os.environ.get('TWITTER_API_SECRET'),
access_token_key=os.environ.get('TWITTER_ACCESS_KEY'),
access_token_secret=os.environ.get('TWITTER_ACCESS_SECRET'))
api.UpdateBanner(filename)
def create_thumb_py(self, mode=None, pth=None):
""" Create the thumbnail using SmartCrop.py """
if pth is None:
raise ValueError("path can't be None")
# Load smartcrop and set options
sc = smartcrop.SmartCrop()
crop_options = smartcrop.DEFAULTS
# Get desired dimensions
nwidth, nheight = self.resize_dims(mode)
crop_options['width'] = nwidth
crop_options['height'] = nheight
# Fix image mode if necessary
img = self.open_original()
if not img.mode in ['RGB', 'RGBA']:
newimg = Image.new('RGB', img.size)
newimg.paste(img)
img = newimg
# Calculate the optimal crop size
ret = sc.crop(img, crop_options)
box = (ret['topCrop']['x'],
ret['topCrop']['y'],
ret['topCrop']['width'] + ret['topCrop']['x'],
ret['topCrop']['height'] + ret['topCrop']['y'])
# Do the actual crop
img = self.open_original()
nimg = img.crop(box)
nimg.thumbnail((nwidth, nheight), Image.ANTIALIAS)
# Create the filename and save the thumbnail
if settings.output_format == 'jpg':
nimg.save(pth, optimize=settings.jpeg_optimize,
progressive=settings.jpeg_progressive,
quality=settings.jpeg_quality)
else:
nimg.save(pth)
return pth
#!/usr/bin/env python import sys import smartcrop from PIL import Image image = Image.open(sys.argv[1]) sc = smartcrop.SmartCrop() result = sc.crop(image, 100, 100) print(result)
