Upload 12 files

app.py

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+import gradio as gr
+import tensorflow as tf
+import gdown
+from PIL import Image
+
+import requests
+
+API_URL = "https://api-inference.huggingface.co/models/facebook/detr-resnet-50-panoptic"
+headers = {"Authorization": "Bearer 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"}
+
+
+
+output = query("cats.jpg")
+
+
+# Perform image segmentation for multy class output
+def query(inputs):
+    with open(inputs, "rb") as f:
+        data = f.read()
+    response = requests.post(API_URL, headers=headers, data=data)
+    return response.json()
+
+
+inputs = gr.inputs.Image(type="pil", label="Upload an image")
+# outputs = gr.outputs.HTML() #uncomment for single class output 
+#outputs = query(inputs)
+
+title = "<h1 style='text-align: center;'>Image Segmentation</h1>"
+description = "Upload an image and get the segmentation result."
+
+gr.Interface(fn=classify_image, 
+             inputs=inputs, 
+             outputs=query(inputs), 
+             title=title, 
+             examples=[["00_plane.jpg"], ["01_car.jpg"], ["02_bird.jpg"], ["03_cat.jpg"], ["04_deer.jpg"]],
+             description=description,
+             enable_queue=True).launch()

requirements.txt

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+gradio