added input validation

README.md

@@ -11,3 +11,18 @@ short_description: sam2 images and video inference on ZeroGPU
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Changelog
+
+this huggingspace demo borrows extensively from [SkalskiP/florence-sam](https://huggingface.co/spaces/SkalskiP/florence-sam/tree/main).
+Here are some changes that's noteworthy:
+
+* the `RuntimeError: No available kernel. Aborting execution.` error documented [here](https://github.com/facebookresearch/sam2/issues/48), [here](https://huggingface.co/spaces/SkalskiP/florence-sam/discussions/5), and [here](https://github.com/facebookresearch/sam2/issues/100) is fixed with the following lines in `app.py` (see [this commit](https://huggingface.co/spaces/SkalskiP/florence-sam/commit/488d99ebc8b60d6a87b84a545dc0561cfadefc65)) with the `@torch.inference_mode()` and
+`@torch.autocast(device_type="cuda", dtype=torch.bfloat16)` before
+the inference function:
+```python
+torch.autocast(device_type="cuda", dtype=torch.bfloat16).__enter__()
+if torch.cuda.get_device_properties(0).major >= 8:
+    torch.backends.cuda.matmul.allow_tf32 = True
+    torch.backends.cudnn.allow_tf32 = True
+```

app.py

@@ -69,7 +69,17 @@ def detect_image(
     Returns:
         list: a list of masks
     """
-    bboxes = json.loads(bboxes) if isinstance(bboxes, str) else bboxes
+    bboxes = (
+        json.loads(bboxes)
+        if isinstance(bboxes, str) and type(bboxes) != type(None)
+        else bboxes
+    )
+    assert bboxes or points, f"either bboxes or points must be provided."
+    if points:
+        assert len(points) == len(
+            point_labels
+        ), f"{len(points)} points provided but there are {len(point_labels)} labels."
+
     model = load_im_model(variant=variant)
     return run_sam_im_inference(
         model, image=im, bboxes=bboxes, get_pil_mask=False, b64_encode_mask=True