ayoubkirouane commited on
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8639a0a
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Update app.py

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  1. app.py +86 -0
app.py CHANGED
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+ from torch import nn
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+ import numpy as np
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+ from PIL import Image
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+ import gradio as gr
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+ from transformers import AutoFeatureExtractor, SegformerForSemanticSegmentation
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+
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+ def ade_palette():
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+ """ADE20K palette that maps each class to RGB values."""
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+ return [[120, 120, 120], [180, 120, 120], [6, 230, 230], [80, 50, 50],
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+ [4, 200, 3], [120, 120, 80], [140, 140, 140], [204, 5, 255],
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+ [230, 230, 230], [4, 250, 7], [224, 5, 255], [235, 255, 7],
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+ [150, 5, 61], [120, 120, 70], [8, 255, 51], [255, 6, 82],
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+ [143, 255, 140], [204, 255, 4], [255, 51, 7], [204, 70, 3],
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+ [0, 102, 200], [61, 230, 250], [255, 6, 51], [11, 102, 255],
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+ [255, 7, 71], [255, 9, 224], [9, 7, 230], [220, 220, 220],
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+ [255, 9, 92], [112, 9, 255], [8, 255, 214], [7, 255, 224],
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+ [255, 184, 6], [10, 255, 71], [255, 41, 10], [7, 255, 255],
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+ [224, 255, 8], [102, 8, 255], [255, 61, 6], [255, 194, 7],
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+ [255, 122, 8], [0, 255, 20], [255, 8, 41], [255, 5, 153],
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+ [6, 51, 255], [235, 12, 255], [160, 150, 20], [0, 163, 255],
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+ [140, 140, 140], [250, 10, 15], [20, 255, 0], [31, 255, 0],
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+ [255, 31, 0], [255, 224, 0], [153, 255, 0], [0, 0, 255],
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+ [255, 71, 0], [0, 235, 255], [0, 173, 255], [31, 0, 255],
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+ [11, 200, 200], [255, 82, 0], [0, 255, 245], [0, 61, 255],
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+ [0, 255, 112], [0, 255, 133], [255, 0, 0], [255, 163, 0],
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+ [255, 102, 0], [194, 255, 0], [0, 143, 255], [51, 255, 0],
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+ [0, 82, 255], [0, 255, 41], [0, 255, 173], [10, 0, 255],
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+ [173, 255, 0], [0, 255, 153], [255, 92, 0], [255, 0, 255],
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+ [255, 0, 245], [255, 0, 102], [255, 173, 0], [255, 0, 20],
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+ [255, 184, 184], [0, 31, 255], [0, 255, 61], [0, 71, 255],
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+ [255, 0, 204], [0, 255, 194], [0, 255, 82], [0, 10, 255],
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+ [0, 112, 255], [51, 0, 255], [0, 194, 255], [0, 122, 255],
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+ [0, 255, 163], [255, 153, 0], [0, 255, 10], [255, 112, 0],
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+ [143, 255, 0], [82, 0, 255], [163, 255, 0], [255, 235, 0],
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+ [8, 184, 170], [133, 0, 255], [0, 255, 92], [184, 0, 255],
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+ [255, 0, 31], [0, 184, 255], [0, 214, 255], [255, 0, 112],
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+ [92, 255, 0], [0, 224, 255], [112, 224, 255], [70, 184, 160],
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+ [163, 0, 255], [153, 0, 255], [71, 255, 0], [255, 0, 163],
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+ [255, 204, 0], [255, 0, 143], [0, 255, 235], [133, 255, 0],
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+ [255, 0, 235], [245, 0, 255], [255, 0, 122], [255, 245, 0],
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+ [10, 190, 212], [214, 255, 0], [0, 204, 255], [20, 0, 255],
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+ [255, 255, 0], [0, 153, 255], [0, 41, 255], [0, 255, 204],
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+ [41, 0, 255], [41, 255, 0], [173, 0, 255], [0, 245, 255],
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+ [71, 0, 255], [122, 0, 255], [0, 255, 184], [0, 92, 255],
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+ [184, 255, 0], [0, 133, 255], [255, 214, 0], [25, 194, 194],
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+ [102, 255, 0], [92, 0, 255]]
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+
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+
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+
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+
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+ def run(img):
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+ extractor = AutoFeatureExtractor.from_pretrained("ayoubkirouane/Segments-Sidewalk-SegFormer-B0")
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+ model = SegformerForSemanticSegmentation.from_pretrained("ayoubkirouane/Segments-Sidewalk-SegFormer-B0")
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+ pixel_values = extractor(img, return_tensors="pt").pixel_values.to("cpu")
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+ outputs = model(pixel_values)
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+ logits = outputs.logits
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+ logits = nn.functional.interpolate(outputs.logits.detach().cpu(),
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+ size=img.size[::-1], # (height, width)
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+ mode='bilinear',
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+ align_corners=False)
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+ # Second, apply argmax on the class dimension
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+ seg = logits.argmax(dim=1)[0]
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+ color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8) # height, width, 3
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+ palette = np.array(ade_palette())
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+ for label, color in enumerate(palette):
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+ color_seg[seg == label, :] = color
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+ # Convert to BGR
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+ color_seg = color_seg[..., ::-1]
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+
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+ # Show image + mask
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+ img = np.array(img) * 0.5 + color_seg * 0.5
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+ img = img.astype(np.uint8)
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+ img = Image.fromarray(img)
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+ return img
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+ # Create a Gradio interface
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+ iface = gr.Interface(
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+ fn=run,
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+ inputs=gr.Image(label="Input image", type="pil"),
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+ examples=["1.png"] ,
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+ outputs=gr.Image(label="Output image with predicted instance Masks", type="pil"),
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+ title="Image Segmentation with Segments-Sidewalk-SegFormer-B0",
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+ description="Upload an image, and this app will perform image segmentation and display the result",
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+ )
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+
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+ # Launch the app
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+ iface.launch(share=True , debug=True)