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import os
os.system("hub install deoldify==1.0.1")
import gradio as gr
import paddlehub as hub
from pathlib import Path
from datetime import datetime
from typing import Optional
model = hub.Module(name='deoldify')
# NOTE: Max is 45 with 11GB video cards. 35 is a good default
render_factor=35
def colorize_image(image):
# now = datetime.now().strftime("%Y%m%d-%H%M%S-%f")
if not os.path.exists("./output"):
os.makedirs("./output")
# if image is not None:
# image.save(f"./output/{now}-input.jpg")
model.predict(image.name)
return f'./output/DeOldify/'+Path(image.name).stem+".png"
# def inference(img, version, scale, weight):
def inference(img, version, scale):
# weight /= 100
print(img, version, scale)
try:
extension = os.path.splitext(os.path.basename(str(img)))[1]
img = cv2.imread(img, cv2.IMREAD_UNCHANGED)
if len(img.shape) == 3 and img.shape[2] == 4:
img_mode = 'RGBA'
elif len(img.shape) == 2: # for gray inputs
img_mode = None
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
else:
img_mode = None
h, w = img.shape[0:2]
if h < 300:
img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
try:
# _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)
_, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
except RuntimeError as error:
print('Error', error)
try:
if scale != 2:
interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS4
h, w = img.shape[0:2]
output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)
except Exception as error:
print('wrong scale input.', error)
if img_mode == 'RGBA': # RGBA images should be saved in png format
extension = 'png'
else:
extension = 'jpg'
save_path = f'output/out.{extension}'
cv2.imwrite(save_path, output)
output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
return output, save_path
except Exception as error:
print('global exception', error)
return None, None
demo = gr.Interface(
inference, [
gr.inputs.Image(type="filepath", label="Input"),
# gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'], type="value", default='v1.4', label='version'),
gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer','CodeFormer','RealESR-General-x4v3'], type="value", default='v1.4', label='version'),
gr.inputs.Number(label="Rescaling factor", default=2),
# gr.Slider(0, 100, label='Weight, only for CodeFormer. 0 for better quality, 100 for better identity', default=50)
], [
gr.outputs.Image(type="numpy", label="Output (The whole image)"),
gr.outputs.File(label="Download the output image")
],
title=title,
description=description,
article=article,
# examples=[['AI-generate.jpg', 'v1.4', 2, 50], ['lincoln.jpg', 'v1.4', 2, 50], ['Blake_Lively.jpg', 'v1.4', 2, 50],
# ['10045.png', 'v1.4', 2, 50]]).launch()
examples=[['a1.jpg', 'v1.4', 2], ['a2.jpg', 'v1.4', 2], ['a3.jpg', 'v1.4', 2],['a4.jpg', 'v1.4', 2]])
demo.queue(concurrency_count=4)
demo.launch()
def create_interface():
with gr.Blocks() as enhancer:
gr.Markdown("Colorize old black & white photos")
with gr.Column(scale=1, label = "Colorize photo", visible=True) as colorize_column:
colorize_input = gr.Image(type="file")
colorize_button = gr.Button("Colorize!")
colorize_output = gr.outputs.Image(type="numpy", label="Output (The Colorized image)")
download_colorize_button = gr.outputs.File(label="Download the colorized image!")
colorize_button.click(colorize_image, inputs=colorize_input, outputs=colorize_output)
enhancer.launch()
def run_code():
create_interface()
# The main function
run_code() |