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")