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)