def apply_model_to_image_raw_bytes(img): # img = utils.decode_image_from_buf(raw) # fig = plt.figure(figsize=(7, 7)) # plt.grid('off') # plt.axis('off') # plt.imshow(img) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) # print(' '.join(generate_caption(img)[1:-1])) return str(' '.join(generate_caption(img)[1:-1]))
def apply_model_to_image_raw_bytes(raw, sample=False): img = utils.decode_image_from_buf(raw) plt.figure(figsize=(7, 7)) plt.grid('off') plt.axis('off') plt.imshow(img) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) print(' '.join(generate_caption(img, sample=sample)[1:-1])) plt.show()
def apply_model_to_image_raw_bytes(raw, fname=None, do_save=False): img = utils.decode_image_from_buf(raw) fig = plt.figure(figsize=(7, 7)) plt.grid('off') plt.axis('off') plt.imshow(img) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) plt.title(' '.join(generate_caption(img)[1:-1])) if do_save: plt.savefig(fname) plt.show()
def apply_model_to_image_raw_bytes(raw): img = utils.decode_image_from_buf(raw) plt.figure(figsize=(7, 7)) plt.grid('off') plt.axis('off') plt.imshow(img) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), generator_model.process_for_model) img = np.expand_dims(img, axis=0) title = generate_caption(img)[1:-1] plt.title(' '.join(title)) plt.show()
def show_valid_example_series(val_img_fns, index_array): all_files = set(val_img_fns) found_files = list( filter(lambda x: x.filename.rsplit("/")[-1] in all_files, zf.filelist)) #plt.figure() index = 1 for row in range(index_array.shape[0]): for col in range(index_array.shape[1]): fn = found_files[index_array[row, col]] img = utils.decode_image_from_buf(zf.read(fn)) subplot = plt.subplot(index_array.shape[0], index_array.shape[1], index) subplot.axis('off') subplot.grid('off') plt.imshow(img) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), generator_model.process_for_model) img_s = np.expand_dims(img, axis=0) title = generate_caption(img_s, sample=False)[1:-1] subplot.set_title(" ".join(title)) index += 1 plt.show()
def apply_model_to_image_raw_bytes(raw): img = utils.decode_image_from_buf(raw) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) print(' '.join(generate_caption(img)[1:-1]))
def apply_model_to_image_raw_bytes_return_next_word_probs(raw, par_caption): img = utils.decode_image_from_buf(raw) img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) return generate_next_word_probs(img, par_caption)
def apply_model_to_image(fname): img = imread(fname)[:,:,:3] img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), final_model.preprocess_for_model) return (' '.join(generate_caption(img)[1:-1]))
def get_caption(img): img = utils.crop_and_preprocess(img, (IMG_SIZE, IMG_SIZE), generator_model.process_for_model) img = np.expand_dims(img, axis=0) return generate_caption(img)[1:-1]