def results():
emotion = request.form["emotion"]
quote = model.get_quote(emotion)
imageSrc = model.get_image(emotion)
return render_template('results.html',
quote=quote[0],
quoteAuthor=quote[1],
imgSrc=imageSrc,
time=datetime.now())
def main():
log(clear=True)
print("Making ascii art out of {} with font {} \n".format(img_file, font_file))
print("Making Font Features...")
vocab, features = make_features(font_file,invert=False, layer_name=layer_name)
print("Making ConvNet Model...")
model = make_model(features, layer_name, pooling)
print("Converting Image...")
img = get_image(img_file)[None, ...]
output = model.predict(img)
correlated_pixels = np.argmax(output, axis=-1).squeeze()
for row in range(0, correlated_pixels.shape[0], 2):
line = ''
for col in range(0, correlated_pixels.shape[1], 1):
line += vocab[correlated_pixels[row, col]]
print(line)
def _to_row(emoticon):
row = {
'name': emoticon.name,
'url': emoticon.url,
'added_by': emoticon.added_by,
'image': None,
'added': None,
}
if emoticon.url.startswith('http'):
image = model.get_image(emoticon.url)
row.update({
'image': image.raw_data,
'added': image.created,
})
return row
def execute_image_deallocation(name: str,
id: int,
new_name: str,
axis: int = 0) -> bool:
"""
Executes image task with given data params, saves resulting images in directory and adds paths to meta.
:param name: Name of image
:param id: Id of image
:param new_name: New name of which image should be generated
:param axis: 0 for horizontal and 1 for vertical
:return: Boolean whether task was successful or not
"""
data: Dict[str, any] = get_image(name, id)
if data is None:
return False
imgs: List[ndarray] = deallocate_img(data, new_name, axis)
directory: str = "new_img/%s/%i/%s/%i/" % (name, id, new_name, axis)
directories: List[str] = save_images(imgs, directory)
add_new_image(name, id, new_name, directories, axis)
return True
def inference():
global result
image = model.get_image(fname)
result, ic, p = l.predict(image)
return redirect(url_for("index"))
def get(self, query_string):
images = model.get_image_search_list(query_string)
if len(images) > 0:
respond_image(model.get_image(images[0]), self.response)
else:
self.redirect("/static/notfound.jpg")
def get(self, file_name):
image = model.get_image(file_name)
if image:
respond_image(image, self.response)
else:
self.redirect("/static/unexplainable.jpg")
