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app.py
CHANGED
@@ -6,12 +6,14 @@ import torch
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from random import randint
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import sys
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from subprocess import call
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# Updating Gradio to a more current version
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# os.system("pip install gradio")
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torch.hub.download_url_to_file('http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution_files/100075_lowres.jpg', 'bear.jpg')
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def run_cmd(command):
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try:
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print(command)
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@@ -19,33 +21,35 @@ def run_cmd(command):
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except KeyboardInterrupt:
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print("Process interrupted")
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sys.exit(1)
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run_cmd("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P .")
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run_cmd("pip install basicsr")
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run_cmd("pip freeze")
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os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P .")
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_id = randint(1, 10000)
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INPUT_DIR =
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OUTPUT_DIR =
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run_cmd(
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run_cmd(
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run_cmd(
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img.
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if mode == "base":
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run_cmd(
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else:
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os.system(
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return os.path.join(OUTPUT_DIR, "1_out.png")
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title = "Real-ESRGAN"
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description = "Gradio demo for Real-ESRGAN. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/xinntao/Real-ESRGAN'>Github Repo</a></p>"
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from random import randint
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import sys
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from subprocess import call
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import psutil
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torch.hub.download_url_to_file('http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution_files/100075_lowres.jpg', 'bear.jpg')
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def run_cmd(command):
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try:
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print(command)
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except KeyboardInterrupt:
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print("Process interrupted")
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sys.exit(1)
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run_cmd("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P .")
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run_cmd("pip install basicsr")
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run_cmd("pip freeze")
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os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P .")
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def inference(img,mode):
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_id = randint(1, 10000)
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INPUT_DIR = "./tmp/input_image" + str(_id) + "/"
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OUTPUT_DIR = "./tmp/output_image" + str(_id) + "/"
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run_cmd("rm -rf " + INPUT_DIR)
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run_cmd("rm -rf " + OUTPUT_DIR)
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run_cmd("mkdir -p " + INPUT_DIR)
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run_cmd("mkdir -p " + OUTPUT_DIR)
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basewidth = 256
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wpercent = (basewidth/float(img.size[0]))
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hsize = int((float(img.size[1])*float(wpercent)))
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#img = img.resize((basewidth,hsize), Image.LANCZOS)
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img.save(INPUT_DIR + "1.png", "PNG")
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if mode == "base":
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run_cmd("python inference_realesrgan.py -n RealESRGAN_x4plus -i "+ INPUT_DIR + " -o " + OUTPUT_DIR)
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else:
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os.system("python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i "+ INPUT_DIR + " -o " + OUTPUT_DIR)
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return os.path.join(OUTPUT_DIR, "1_out.png")
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title = "Real-ESRGAN"
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description = "Gradio demo for Real-ESRGAN. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/xinntao/Real-ESRGAN'>Github Repo</a></p>"
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