Update app.py

app.py

@@ -1,69 +0,0 @@
-import os
-import random
-os.system("pip install gradio==2.9b23")
-import gradio as gr
-from PIL import Image
-import torch
-from subprocess import call
-
-# Install necessary packages
-os.system("pip install gradio==2.9b23")
-os.system("pip install basicsr")
-os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P .")
-os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P .")
-
-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')
-
-def run_cmd(command):
-    try:
-        print(command)
-        call(command, shell=True)
-    except KeyboardInterrupt:
-        print("Process interrupted")
-        sys.exit(1)
-
-def inference(img, mode):
-    _id = random.randint(1, 10000)
-    INPUT_DIR = "/tmp/input_image" + str(_id) + "/"
-    OUTPUT_DIR = "/tmp/output_image" + str(_id) + "/"
-    run_cmd("rm -rf " + INPUT_DIR)
-    run_cmd("rm -rf " + OUTPUT_DIR)
-    run_cmd("mkdir " + INPUT_DIR)
-    run_cmd("mkdir " + OUTPUT_DIR)
-    
-    basewidth = 256
-    wpercent = (basewidth / float(img.size[0]))
-    hsize = int((float(img.size[1]) * float(wpercent)))
-    img = img.resize((basewidth, hsize), Image.LANCZOS)
-    img.save(INPUT_DIR + "1.jpg", "JPEG")
-    
-    if mode == "base":
-        run_cmd("python inference_realesrgan.py -n RealESRGAN_x4plus -i " + INPUT_DIR + " -o " + OUTPUT_DIR)
-    else:
-        run_cmd("python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i " + INPUT_DIR + " -o " + OUTPUT_DIR)
-    
-    return os.path.join(OUTPUT_DIR, "1_out.jpg")
-
-def main():
-    with gr.Blocks() as demo:
-        gr.Markdown("# Real-ESRGAN")
-        gr.Markdown(
-            "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."
-            "\n\n"
-            "<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>"
-        )
-        
-        with gr.Row():
-            with gr.Column():
-                input_image = gr.Image(type="pil", label="Input")
-                model_type = gr.Radio(["base", "anime"], type="value", default="base", label="Model type")
-                examples = gr.Examples(examples=[['bear.jpg', 'base'], ['anime.png', 'anime']], inputs=[input_image, model_type])
-                submit_btn = gr.Button("Submit")
-            
-            with gr.Column():
-                output_image = gr.Image(type="file", label="Output")
-
-        submit_btn.click(fn=inference, inputs=[input_image, model_type], outputs=output_image)
-    
-    demo.launch()
-