Update test README with implementation status

tests/README.md

@@ -1,6 +1,6 @@
 # FoundationPose Tests
 
-This directory contains test scripts for the FoundationPose estimator.
+This directory contains test scripts for the FoundationPose HuggingFace API.
 
 ## Test Data
 
@@ -8,26 +8,64 @@ Reference images for test objects are stored in `reference/target_cube/`.
 
 ## Running Tests
 
-### Test Estimator Locally
+### Test Against HuggingFace Space
 
 ```bash
 cd /path/to/foundationpose
-python tests/test_estimator.py
+/path/to/training/.venv/bin/python tests/test_estimator.py
 ```
 
-### Test Against HuggingFace Space
-
-Use the client script to test the deployed API:
-
-```bash
-python client.py
-```
+The test uses the Gradio client to connect to the deployed API.
 
 ## Test Coverage
 
 **test_estimator.py** tests:
-1. Estimator initialization
-2. Object registration with reference images
+1. API client initialization
+2. Object initialization via API (reference-based)
 3. Pose estimation on query images
 
-The test uses images from `reference/target_cube/` to register an object, then randomly selects one image to test pose estimation.
+## Current Status
+
+**CAD-Based Mode**: ✅ Fully Implemented
+- Requires a 3D mesh file (.obj, .stl, .ply)
+- Provides accurate 6D pose estimation
+- Use the CAD-Based initialization tab in the Gradio interface
+
+**Model-Free Mode**: ⚠️ Not Yet Implemented
+- Would require 3D reconstruction from reference images (photogrammetry)
+- For now, use photogrammetry tools (Meshroom, COLMAP) to create a mesh first
+- Then use CAD-Based mode with the generated mesh
+
+## API Usage
+
+The deployed Space provides two Gradio API endpoints:
+
+### CAD-Based Initialization
+```python
+from gradio_client import Client, handle_file
+
+client = Client("https://gpue-foundationpose.hf.space")
+
+result = client.predict(
+    object_id="my_object",
+    mesh_file=handle_file("object.obj"),
+    reference_files=[handle_file(f) for f in image_files],  # Optional
+    fx=500.0, fy=500.0, cx=320.0, cy=240.0,
+    api_name="/gradio_initialize_cad"
+)
+```
+
+### Pose Estimation
+```python
+result = client.predict(
+    object_id="my_object",
+    query_image=handle_file("query.jpg"),
+    fx=500.0, fy=500.0, cx=320.0, cy=240.0,
+    api_name="/gradio_estimate"
+)
+```
+
+## Known Issues
+
+1. **Model-Free Mode**: Reference-only initialization is not yet supported. A 3D mesh is required.
+2. **Test Results**: Current tests will return "No poses detected" because they don't provide a mesh file.