uploaded initial files

README.md

@@ -1,6 +1,6 @@
 ---
 title: ASL Detector YOLOV9
-emoji: 🐠
+emoji: ✊🏼
 colorFrom: red
 colorTo: gray
 sdk: gradio

app.py

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+import spaces
+import PIL.Image as Image
+import gradio as gr
+from ultralytics import ASSETS, YOLO
+
+
+model = YOLO("best.pt")
+
+@spaces.GPU
+def predict_image(img, conf_threshold, iou_threshold):
+    results = model.predict(
+        source=img,
+        device="cuda:0",
+        conf=conf_threshold,
+        iou=iou_threshold,
+        show_labels=True,
+        show_conf=True,
+        imgsz=416,
+        max_det=1
+    )
+
+    for r in results:
+        im_array = r.plot()
+        im = Image.fromarray(im_array[..., ::-1])
+
+    return im
+
+
+asl = gr.Interface(
+    fn=predict_image,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
+        gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold")
+    ],
+    outputs=gr.Image(type="pil", label="Result"),
+    title="ASL Detector YOLOv9e",
+    description="Upload images for inference. The Ultralytics YOLOv9e model is used by default. Letter Z is not supported.",
+    examples=[
+        [ASSETS / "a.jpg", 0.25, 0.45],
+        [ASSETS / "b.jpg", 0.25, 0.45],
+    ]
+)
+
+if __name__ == '__main__':
+    asl.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4dab1e073a4a428e1f26aa5b0864a0e93094519737f4efeb64cadd986958e0bc
+size 117279194