Spaces:

codeslake
/

RefVSR

Runtime error

App Files Files Community

RefVSR / app.py

codeslake

Update app.py

c18ed86 about 2 years ago

raw history blame contribute delete

No virus

8.16 kB

	import os
	import sys
	import gradio as gr
	from PIL import Image

	## environment settup
	os.system("git clone https://github.com/codeslake/RefVSR.git")
	os.chdir("RefVSR")
	os.system("./install/install_cudnn113.sh")
	os.mkdir("ckpt")
	os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/SPyNet.pytorch -O ckpt/SPyNet.pytorch")

	os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_MFID_8K.pytorch -O ckpt/RefVSR_MFID_8K.pytorch")
	os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch -O ckpt/RefVSR_small_MFID_8K.pytorch")

	os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_MFID.pytorch -O ckpt/RefVSR_MFID.pytorch")
	os.system("wget https://huggingface.co/spaces/codeslake/RefVSR/resolve/main/RefVSR_small_MFID_8K.pytorch -O ckpt/RefVSR_small_MFID.pytorch")

	sys.path.append("RefVSR")

	## I/O setup (creates folders and places inputs corresponding to the original RefVSR code)
	# HD input
	HR_LR_path = "test/RealMCVSR/test/HR/UW/0000"
	HR_Ref_path = "test/RealMCVSR/test/HR/W/0000"
	HR_Ref_path_T = "test/RealMCVSR/test/HR/T/0000"
	os.makedirs(HR_LR_path)
	os.makedirs(HR_Ref_path)
	os.makedirs(HR_Ref_path_T)
	os.system("wget https://www.dropbox.com/s/x33ka2jlzwsde7r/LR.png -O HR_LR1.png")
	os.system("wget https://www.dropbox.com/s/pp903wlz3syf68w/Ref.png -O HR_Ref1.png")
	os.system("wget https://www.dropbox.com/s/zl0h83x0le6ejfw/LR.png -O HR_LR2.png")
	os.system("wget https://www.dropbox.com/s/9hzupmc3clt0f0e/Ref.png -O HR_Ref2.png")
	os.system("wget https://www.dropbox.com/s/2u6lcfdhvcylklg/LR.png -O HR_LR3.png")
	os.system("wget https://www.dropbox.com/s/a7bwfy3gl26tvbq/Ref.png -O HR_Ref3.png")

	# 4x downsampled input
	LR_path = "test/RealMCVSR/test/LRx4/UW/0000"
	Ref_path = "test/RealMCVSR/test/LRx4/W/0000"
	Ref_path_T = "test/RealMCVSR/test/LRx4/T/0000"
	os.makedirs(LR_path)
	os.makedirs(Ref_path)
	os.makedirs(Ref_path_T)
	os.system("wget https://www.dropbox.com/s/hkvdwm3grshjt0k/LR.png -O LR.png")
	os.system("wget https://www.dropbox.com/s/4sv34su3kg1ifkp/Ref.png -O Ref.png")

	# output directory
	os.makedirs('result')

	## resize if necessary (not used)
	def resize(img):
	max_side = 480
	w = img.size[0]
	h = img.size[1]
	if max(h, w) > max_side:
	scale_ratio = max_side / max(h, w)
	wsize=int(w*scale_ratio)
	hsize=int(h*scale_ratio)
	img = img.resize((wsize,hsize), Image.ANTIALIAS)
	w = img.size[0]
	h = img.size[1]
	img = img.crop((0, 0, w-w%8, h-h%8))

	return img


	#################### 8K ##################
	## inference
	def inference_8K(LR, Ref):
	## resize for user selected input (not used)
	LR = resize(LR)
	Ref = resize(Ref)

	## Input setup (creates folders and places inputs corresponding to the original RefVSR code)
	LR.save(os.path.join(LR_path, '0000.png'))
	Ref.save(os.path.join(Ref_path, '0000.png'))
	Ref.save(os.path.join(Ref_path_T, '0000.png'))
	LR.save(os.path.join(HR_LR_path, '0000.png'))
	Ref.save(os.path.join(HR_Ref_path, '0000.png'))
	Ref.save(os.path.join(HR_Ref_path_T, '0000.png'))

	## Run RefVSR model
	os.system("python -B run.py \
	--mode RefVSR_MFID_8K \
	--config config_RefVSR_MFID_8K \
	--data RealMCVSR \
	--ckpt_abs_name ckpt/RefVSR_MFID_8K.pytorch \
	--data_offset ./test \
	--output_offset ./result \
	--qualitative_only \
	--cpu \
	--is_gradio")
	return "result/0000.png"

	title="RefVSR"
	description="Demo application for Reference-based Video Super-Resolution (RefVSR). Upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively. The demo runs on CPUs and takes about 30s."

	article = "<p style='text-align: center'><b>To check the full capability of the module, we recommend to clone Github repository and run RefVSR models on videos using GPUs.</b></p><p style='text-align: center'>This demo runs on CPUs and only supports RefVSR for a single LR and Ref frames due to computational complexity.<br>Hence, the model <b>will not take advantage</b> of temporal LR and Ref frames.</p><p style='text-align: center'>Moreover, the model is trained <b>with the proposed 2-stage training strategy</b>, but due to the memory and computational complexity, we downsampled sample frames to have the 480x270 resolution.</p><p style='text-align: center'>For user given frames, the size will be adjusted for the longer side of the frames to have 480 pixels.</p><p style='text-align: center'><a href='https://junyonglee.me/projects/RefVSR' target='_blank'>Project</a> \| <a href='https://arxiv.org/abs/2203.14537' target='_blank'>arXiv</a> \| <a href='https://github.com/codeslake/RefVSR' target='_blank'>Github</a></p>"

	## resize for sample (not used)
	#LR = resize(Image.open('LR.png')).save('LR.png')
	#Ref = resize(Image.open('Ref.png')).save('Ref.png')

	## input
	examples=[['HR_LR1.png', 'HR_Ref1.png'], ['HR_LR2.png', 'HR_Ref2.png'], ['HR_LR3.png', 'HR_Ref3.png']]

	## interface
	gr.Interface(inference_8K,[gr.inputs.Image(type="pil"), gr.inputs.Image(type="pil")],gr.outputs.Image(type="file"),title=title,description=description,article=article,theme ="peach",examples=examples).launch(enable_queue=True)

	#################### low res ##################
	## inference
	def inference(LR, Ref):
	## resize for user selected input
	LR = resize(LR)
	Ref = resize(Ref)

	## Input setup (creates folders and places inputs corresponding to the original RefVSR code)
	LR.save(os.path.join(LR_path, '0000.png'))
	Ref.save(os.path.join(Ref_path, '0000.png'))
	Ref.save(os.path.join(Ref_path_T, '0000.png'))
	LR.save(os.path.join(HR_LR_path, '0000.png'))
	Ref.save(os.path.join(HR_Ref_path, '0000.png'))
	Ref.save(os.path.join(HR_Ref_path_T, '0000.png'))

	## Run RefVSR model
	os.system("python -B run.py \
	--mode RefVSR_MFID \
	--config config_RefVSR_MFID \
	--data RealMCVSR \
	--ckpt_abs_name ckpt/RefVSR_MFID.pytorch \
	--data_offset ./test \
	--output_offset ./result \
	--qualitative_only \
	--cpu \
	--is_gradio")
	return "result/0000.png"

	title="Demo for RefVSR (CVPR 2022)"
	description="The demo applies 4xVSR on a video frame. It runs on CPUs and takes about 150s. For the demo, upload a low-resolution frame and a reference frame to 'LR' and 'Ref' input windows, respectively. It is recommended for the reference frame to have a 2x larger zoom factor than that of the low-resolution frame."

	article = "<p style='text-align: center'><b>To check the full capability of the module, we recommend to clone Github repository and run RefVSR models on videos using GPUs.</b></p><p style='text-align: center'>This demo runs on CPUs and only supports RefVSR for a single LR and Ref frames due to computational complexity.<br>Hence, the model <b>will not take advantage</b> of temporal LR and Ref frames.</p><p style='text-align: center'>Moreover, the model is trained <b>only with the proposed pre-training strategy</b> to cope with downsampled sample frames, which are in the 480x270 resolution.</p><p style='text-align: center'>For user given frames, the size will be adjusted for the longer side of the frames to have 480 pixels.</p><p style='text-align: center'><a href='https://junyonglee.me/projects/RefVSR' target='_blank'>Project</a> \| <a href='https://arxiv.org/abs/2203.14537' target='_blank'>arXiv</a> \| <a href='https://github.com/codeslake/RefVSR' target='_blank'>Github</a></p>"

	## resize for sample
	LR = resize(Image.open('LR.png')).save('LR.png')
	Ref = resize(Image.open('Ref.png')).save('Ref.png')

	## input
	examples=[['LR.png','Ref.png']]

	## interface
	gr.Interface(inference, [gr.inputs.Image(type="pil"), gr.inputs.Image(type="pil")], gr.outputs.Image(type="file"),title=title,description=description,article=article,theme ="peach",examples=examples).launch(enable_queue=True)