add space

app.py

@@ -0,0 +1,38 @@
+import tempfile
+
+import gradio as gr
+from autodistill_fastvit import FASTVIT_IMAGENET_1K_CLASSES, FastViT
+from PIL import Image
+
+base_model = FastViT(None)
+
+
+def infer(image):
+    with tempfile.NamedTemporaryFile(suffix=".jpg") as temp:
+        image = Image.fromarray(image.astype("uint8"), "RGB")
+
+        image.save(temp.name)
+
+        predictions = base_model.predict(temp.name, confidence=0.1)
+
+        labels = [FASTVIT_IMAGENET_1K_CLASSES[i] for i in predictions.class_id.tolist()]
+        confidences = predictions.confidence.tolist()
+
+        # divide by 100 to convert to percentage
+        confidences = [c / 100 for c in confidences]
+
+        return {
+            k: v
+            for k, v in zip(labels, confidences)
+        }
+
+
+iface = gr.Interface(
+    fn=infer,
+    inputs="image",
+    outputs="label",
+    allow_flagging=False,
+    title="FastViT",
+    description="[FastViT](https://github.com/apple/ml-fastvit) is a fast Vision Transformer developed by Apple. FastViT was trained on the ImageNet-1k dataset.\n\nUse the space below to test FastViT on your own images.\n\nThis space uses [Autodistill FastViT](https://github.com/autodistill/autodistill-fastvit) for inference.",
+)
+iface.launch()