def test_missing_model():
"""
Try to load a filter that doesn't exists.
Raise KeyError
"""
with pytest.raises(KeyError):
Instafilter("xxx")
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
def test_missing_image():
"""
Try to filter an image that doesn't exist.
Raise FileNotFoundError
"""
model = Instafilter("Lo-Fi")
with pytest.raises(OSError):
model("xxx")
def test_filter_image():
"""
Filter an image. Check that it changed.
"""
model = Instafilter("Lo-Fi")
f_image = __local__ / "Normal.jpg"
img0 = cv2.imread(str(f_image))
img1 = model(f_image)
diff = (img0 - img1).sum()
assert abs(diff) > 0
def test_RGB_mode():
"""
Filter an image with RGB mode on and off.
Check that we get different results.
"""
model = Instafilter("Lo-Fi")
f_image = __local__ / "Normal.jpg"
img1 = model(f_image)
img2 = model(f_image, is_RGB=True)
diff = (img1 - img2).sum()
assert abs(diff) > 0
def run(mode, image_file):
try:
# read image_file
f_id = str(uuid.uuid4())
f_name = secure_filename(image_file.filename)
image_byte = image_file.read()
image = byte_to_image(image_byte)
# make input&result file folder
paths = [os.path.join(INPUT_DIR, f_id)]
os.makedirs(paths[0], exist_ok=True)
# save image to input folder
in_filename = os.path.join(paths[0], f_name)
image.save(in_filename, quality=100, subsampling=0)
# run model
model = Instafilter(mode)
new_image = model(in_filename)
# convert nparray to image
new_image = cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB)
ouput_image = Image.fromarray(new_image)
# convert result image to byte format
byte_image = image_to_byte(ouput_image)
return byte_image
except Exception as e:
print(e)
return 500
finally:
# remove input folder
if paths:
remove_file(paths)
paths.clear()
from werkzeug.utils import secure_filename
# import for server
from flask import Flask, render_template, request, Response, send_file, jsonify
from queue import Queue, Empty
import threading
import time
# flask server
app = Flask(__name__)
# limit input file size under 2MB
app.config['MAX_CONTENT_LENGTH'] = 2 * 1024 * 1024
# model loading
model = Instafilter('Crema')
# request queue setting
requests_queue = Queue()
BATCH_SIZE = 1
CHECK_INTERVAL = 0.1
# static variable
models = [
'1977', 'Aden', 'Amaro', 'Ashby', 'Brannan', 'Brooklyn', 'Charmes',
'Clarendon', 'Crema', 'Dogpatch', 'Earlybird', 'Gingham', 'Ginza', 'Hefe',
'Helena', 'Hudson', 'Inkwell', 'Juno', 'Kelvin', 'Lark', 'Lo-Fi', 'Ludwig',
'Mayfair', 'Melvin', 'Moon', 'Nashville', 'Perpetua', 'Reyes', 'Rise',
'Sierra', 'Skyline', 'Slumber', 'Stinson', 'Sutro', 'Toaster', 'Valencia',
'Vesper', 'Walden', 'Willow', 'X-ProII'
]
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)