startup_report

app.py

@@ -13,6 +13,8 @@ import matplotlib.pyplot as plt
 from transformers import AutoModelForMaskGeneration, AutoProcessor, pipeline
 import gradio as gr
 import spaces
+import time
+import httpx
 
 @dataclass
 class BoundingBox:
@@ -104,10 +106,26 @@ def refine_masks(masks: torch.BoolTensor, polygon_refinement: bool = False) -> L
             masks[idx] = cv2.fillPoly(np.zeros(shape, dtype=np.uint8), [polygon], 1)
     return list(masks)
 
+def startup_report_with_retries(client, retries=5, delay=2):
+    for i in range(retries):
+        try:
+            client.startup_report()
+            return
+        except httpx.ConnectTimeout:
+            if i < retries - 1:
+                time.sleep(delay)
+            else:
+                raise
+
 @spaces.GPU
 def detect(image: Image.Image, labels: List[str], threshold: float = 0.3, detector_id: Optional[str] = None) -> List[Dict[str, Any]]:
     detector_id = detector_id if detector_id else "IDEA-Research/grounding-dino-base"
     object_detector = pipeline(model=detector_id, task="zero-shot-object-detection", device="cuda")
+
+    # Initialize and call startup report with retries
+    client = httpx.Client()
+    startup_report_with_retries(client)
+
     labels = [label if label.endswith(".") else label+"." for label in labels]
     results = object_detector(image, candidate_labels=labels, threshold=threshold)
     return [DetectionResult.from_dict(result) for result in results]
@@ -198,4 +216,4 @@ gr.Interface(
     inputs=gr.Image(type="pil"),
     outputs=[gr.Image(type="numpy"), gr.Image(type="numpy")],
     title="🐞 InsectSAM + GroundingDINO Inference",
-).launch()
+).launch()