def test_get_model_names(): """ Check that the module loads the list of names and is non-empty. """ names = Instafilter.get_models() assert isinstance(names, list) assert len(names) > 1
from instafilter import Instafilter st.set_option("deprecation.showfileUploaderEncoding", False) st.beta_set_page_config( layout="wide", initial_sidebar_state="expanded", ) url = "https://github.com/thoppe/instafilter" st.markdown("# [Instafilter]({url}) demo") model_name = st.sidebar.selectbox( "Choose a filter", sorted(Instafilter.get_models()), index=20, ) model = Instafilter(model_name) raw_image_bytes = st.file_uploader("Choose an image...") if raw_image_bytes is not None: img0 = np.array(Image.open(raw_image_bytes)) with st.spinner(text="Applying filter..."): # Apply the model, convert to BGR first and after img1 = model(img0[:, :, ::-1], is_RGB=False)[:, :, ::-1] st.image([img1, img0],
import cv2 from pathlib import Path from instafilter import Instafilter scale_size = 0.741 f_source = "train_new_model/input/Normal.jpg" save_dest = Path("examples") save_dest.mkdir(exist_ok=True) img0 = cv2.imread(f_source) for name in Instafilter.get_models(): f_save = save_dest / (name + ".jpg") model = Instafilter(name) img1 = model(f_source) img2 = cv2.resize(img1, None, fx=scale_size, fy=scale_size) print(f"Saving {name}, {img2.shape}") cv2.imwrite(str(f_save), img2)