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Runtime error
FIX loading super resolution repo
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app.py
CHANGED
@@ -1,4 +1,20 @@
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# %%
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import gradio as gr
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example_generated_ape_super = "examples/generated_ape_super_resolution.jpg"
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@@ -13,7 +29,8 @@ examples = [
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]
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ape_gen = gr.Interface.load("spaces/ykilcher/apes")
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super_resolution = gr.Interface.load("spaces/akhaliq/SwinIR")
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style_transfer = gr.Interface.load("spaces/aravinds1811/neural-style-transfer")
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def generate_ape(num_images=1, interpolate=False):
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@@ -28,12 +45,12 @@ def perform_style_transfer(content_image, style_image, is_super_resolution=False
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# %%
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with gr.Blocks() as demo:
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button_generate_ape = gr.Button("Generate Ape")
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generated_ape = gr.Image(example_generated_ape, label="Generated Ape", type="filepath")
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style_image_input = gr.Image(example_style_starry_night, label="Stylish Image", type="filepath")
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style_in_super_resolution = gr.Checkbox(True, label="Super resolution!")
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stylish_ape = gr.Image(example_stylish_ape, label="Stylish Ape")
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gr.Interface(
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fn=perform_style_transfer,
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inputs=[generated_ape, style_image_input, style_in_super_resolution],
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# %%
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import os
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from PIL import Image
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os.system('wget https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth -P experiments/pretrained_models')
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def super_resolution_inference(img):
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os.system('mkdir test')
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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.ANTIALIAS)
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img.save("test/1.jpg", "JPEG")
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os.system('python main_test_swinir.py --task real_sr --model_path experiments/pretrained_models/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth --folder_lq test --scale 4')
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return 'results/swinir_real_sr_x4/1_SwinIR.png'
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# %%
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import gradio as gr
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example_generated_ape_super = "examples/generated_ape_super_resolution.jpg"
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]
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ape_gen = gr.Interface.load("spaces/ykilcher/apes")
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# super_resolution = gr.Interface.load("spaces/akhaliq/SwinIR")
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super_resolution = super_resolution_inference
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style_transfer = gr.Interface.load("spaces/aravinds1811/neural-style-transfer")
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def generate_ape(num_images=1, interpolate=False):
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# %%
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with gr.Blocks() as demo:
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button_generate_ape = gr.Button("Generate Ape")
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generated_ape = gr.Image(example_generated_ape, label="Generated Ape", type="filepath")
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style_image_input = gr.Image(example_style_starry_night, label="Stylish Image", type="filepath")
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style_in_super_resolution = gr.Checkbox(True, label="Super resolution!")
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stylish_ape = gr.Image(example_stylish_ape, label="Stylish Ape")
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gr.Interface(
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fn=perform_style_transfer,
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inputs=[generated_ape, style_image_input, style_in_super_resolution],
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