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| from source.defectGenerator import DefectGenerator | |
| import matplotlib.pyplot as plt | |
| from PIL import Image | |
| import gradio as gr | |
| import numpy as np | |
| def generate_defect_image(image, defect_type,category): | |
| defGen=DefectGenerator(image.size,dtd_path="samples/dtd/") | |
| defect,msk=defGen.genDefect(image,[defect_type],category.lower()) | |
| defect=(defect.permute(1,2,0).numpy()*255.0).astype('uint8') | |
| msk=(msk.permute(1,2,0).numpy()*255.0).astype('uint8') | |
| msk = np.concatenate((msk, msk, msk), axis=2) | |
| return defect, msk | |
| images = { | |
| "Bottle": Image.open('samples/bottle.png').convert('RGB').resize((1024, 1024)), | |
| "Cable": Image.open('samples/cable.png').convert('RGB').resize((1024, 1024)), | |
| "Capsule": Image.open('samples/capsule.png').convert('RGB').resize((1024, 1024)), | |
| "Carpet": Image.open('samples/carpet.png').convert('RGB').resize((1024, 1024)), | |
| "Grid": Image.open('samples/grid.png').convert('RGB').resize((1024, 1024)), | |
| "Hazelnut": Image.open('samples/hazelnut.png').convert('RGB').resize((1024, 1024)), | |
| "Leather": Image.open('samples/leather.png').convert('RGB').resize((1024, 1024)), | |
| "Metal Nut": Image.open('samples/metal_nut.png').convert('RGB').resize((1024, 1024)), | |
| "Pill": Image.open('samples/pill.png').convert('RGB').resize((1024, 1024)), | |
| "Screw": Image.open('samples/screw.png').convert('RGB').resize((1024, 1024)), | |
| "Tile": Image.open('samples/tile.png').convert('RGB').resize((1024, 1024)), | |
| "Toothbrush": Image.open('samples/toothbrush.png').convert('RGB').resize((1024, 1024)), | |
| "Transistor": Image.open('samples/transistor.png').convert('RGB').resize((1024, 1024)), | |
| "Wood": Image.open('samples/wood.png').convert('RGB').resize((1024, 1024)), | |
| "Zipper": Image.open('samples/zipper.png').convert('RGB').resize((1024, 1024)) | |
| } | |
| def generate_and_display_images(category, defect_type): | |
| base_image = images[category] | |
| img_with_defect, defect_mask = generate_defect_image(base_image, defect_type,category) | |
| return np.array(base_image), img_with_defect, defect_mask | |
| # Components | |
| with gr.Blocks(css="style.css") as demo: | |
| gr.HTML( | |
| "<h1><center> 🏭 MVTEC AD Defect Generator 🏭 </center></h1>" + | |
| "<p><center><a href='https://github.com/SimonThomine/IndustrialDefectLib'>https://github.com/SimonThomine/IndustrialDefectLib</a></center></p>" | |
| ) | |
| with gr.Group(): | |
| with gr.Row(): | |
| category_input = gr.Dropdown(label="Select object", choices=list(images.keys()),value="Bottle") | |
| defect_type_input = gr.Dropdown(label="Select type of defect", choices=["blurred", "nsa","structural", "textural","cutpaste" ],value="nsa") | |
| submit = gr.Button( | |
| scale=1, | |
| variant='primary' | |
| ) | |
| with gr.Row(): | |
| with gr.Column(scale=1, min_width=400): | |
| gr.HTML("<h1><center> Base </center></h1>") | |
| base_image_output = gr.Image("Base", type="numpy") | |
| with gr.Column(scale=1, min_width=400): | |
| gr.HTML("<h1><center> Mask </center></h1>") | |
| mask_output = gr.Image("Mask", type="numpy") | |
| with gr.Column(scale=1, min_width=400): | |
| gr.HTML("<h1><center> Defect </center></h1>") | |
| defect_image_output = gr.Image("Defect", type="numpy") | |
| submit.click( | |
| fn=generate_and_display_images, | |
| inputs=[category_input, defect_type_input], | |
| outputs=[base_image_output, defect_image_output,mask_output], | |
| ) | |
| demo.launch() |