Prepare job build context

deploy.sh

@@ -330,9 +330,7 @@ echo "✓ Pushed to HuggingFace"
 echo ""
 echo "HuggingFace will now:"
 echo "  1. Pull base image from DockerHub (${IMAGE_NAME_L2}:${TAG})"
-echo "  2. Build CUDA extensions"
-echo "  3. Download model weights"
-echo "  4. Start the Gradio app"
+echo "  2. Start the Gradio app"
 echo ""
 
 # Follow build logs
@@ -395,7 +393,7 @@ if [ -n "${HF_TOKEN}" ]; then
 
     echo ""
     echo "Following application logs for 1 minute..."
-    LOG_URL="https://huggingface.co/api/spaces/${HF_SPACE}/logs"
+    LOG_URL="https://huggingface.co/api/spaces/${HF_SPACE}/logs/run"
     export LOG_URL
     python3 - <<'PY'
 import os

estimator.py

@@ -5,6 +5,7 @@ This module wraps the FoundationPose library for 6D object pose estimation.
 """
 
 import logging
+import os
 import sys
 from pathlib import Path
 from typing import Dict, List, Optional
@@ -40,7 +41,7 @@ except ImportError as e:
 class FoundationPoseEstimator:
     """Wrapper for FoundationPose model."""
 
-    def __init__(self, device: str = "cuda", weights_dir: str = "weights"):
+    def __init__(self, device: str = "cuda", weights_dir: str | None = None):
         """Initialize FoundationPose estimator.
 
         Args:
@@ -48,6 +49,8 @@ class FoundationPoseEstimator:
             weights_dir: Directory containing model weights
         """
         self.device = device
+        if weights_dir is None:
+            weights_dir = os.environ.get("FOUNDATIONPOSE_WEIGHTS_DIR", "/app/FoundationPose/weights")
         self.weights_dir = Path(weights_dir)
         self.registered_objects = {}
         self.scorer = None