Update app.py

app.py

@@ -1,27 +1,120 @@
-from fastapi import FastAPI
-from dotenv import load_dotenv
-from tasks import text, image, audio
-
-# Load environment variables
-load_dotenv()
-
-app = FastAPI(
-    title="Frugal AI Challenge API",
-    description="API for the Frugal AI Challenge evaluation endpoints"
-)
-
-# Include all routers
-app.include_router(text.router)
-app.include_router(image.router)
-app.include_router(audio.router)
-
-@app.get("/")
-async def root():
-    return {
-        "message": "Welcome to the Frugal AI Challenge API",
-        "endpoints": {
-            "text": "/text - Text classification task",
-            "image": "/image - Image classification task (coming soon)",
-            "audio": "/audio - Audio classification task (coming soon)"
-        }
-    } 
+import gradio as gr
+from ultralytics import YOLO
+
+
+def yolov10_inference(image, model_id, image_size, conf_threshold):
+    model = YOLO(f'{model_id}.engine')
+    results = model.predict(source=image, imgsz=image_size, conf=conf_threshold)
+    annotated_image = results[0].plot()
+    return annotated_image[:, :, ::-1], None
+
+
+def yolov10_inference_for_examples(image, model_path, image_size, conf_threshold):
+    annotated_image, _ = yolov10_inference(image, model_path, image_size, conf_threshold)
+    return annotated_image
+
+
+def app():
+    with gr.Blocks():
+        with gr.Row():
+            with gr.Column():
+                image = gr.Image(type="pil", label="Image", visible=True)
+                model_id = gr.Dropdown(
+                    label="Model",
+                    choices=[
+                        "yolov10s",
+                        "yolov10m",
+                        "yolov10m_ssvd_0.4",
+                        "yolov10m_wsvd_0.4",
+                    ],
+                    value="yolov10s",
+                )
+                image_size = gr.Slider(
+                    label="Image Size",
+                    minimum=320,
+                    maximum=1280,
+                    step=32,
+                    value=640,
+                )
+                conf_threshold = gr.Slider(
+                    label="Confidence Threshold",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.05,
+                    value=0.25,
+                )
+                yolov10_infer = gr.Button(value="Detect Smoke")
+
+            with gr.Column():
+                output_image = gr.Image(type="numpy", label="Annotated Image", visible=True)
+
+        yolov10_infer.click(
+            fn=yolov10_inference,
+            inputs=[image, model_id, image_size, conf_threshold],
+            outputs=[output_image],
+        )
+
+        gr.Examples(
+            examples=[
+                [
+                    "examples/smoke1.jpg",
+                    "yolov10s",
+                    1280,
+                    0.25,
+                ],
+                [
+                    "examples/smoke2.jpg",
+                    "yolov10s",
+                    1280,
+                    0.25,
+                ],
+                [
+                    "examples/smoke3.jpg",
+                    "yolov10s",
+                    1280,
+                    0.25,
+                ],
+                [
+                    "examples/smoke4.jpg",
+                    "yolov10s",
+                    1280,
+                    0.25,
+                ],
+                [
+                    "examples/smoke5.jpg",
+                    "yolov10s",
+                    1280,
+                    0.25,
+                ],
+            ],
+            fn=yolov10_inference_for_examples,
+            inputs=[
+                image,
+                model_id,
+                image_size,
+                conf_threshold,
+            ],
+            outputs=[output_image],
+            cache_examples='lazy',
+        )
+
+gradio_app = gr.Blocks()
+with gradio_app:
+    gr.HTML(
+        """
+    <h1 style='text-align: center'>
+    YOLOv10 for early fire detection with low resource consumption
+    </h1>
+    """)
+    gr.HTML(
+        """
+        <h3 style='text-align: center'>
+        Original paper and code:
+        <a href='https://arxiv.org/abs/2405.14458' target='_blank'>arXiv</a> | <a href='https://github.com/THU-MIG/yolov10' target='_blank'>github</a>
+        </h3>
+        """)
+    with gr.Row():
+        with gr.Column():
+            app()
+if __name__ == '__main__':
+    gradio_app.launch()