Fred Bliss
4a091e9298
- Fixed generateTokens to properly handle different region types (bounding_box, polygon, object_reference) - Added checkbox UI to control includeObjectRef for boxes/polygons - Object references now correctly handle 2 coordinates instead of expecting 4 - Updated Python code to respect includeObjectRef flag from JavaScript - Fixed coordinate format issues (x1,y1,x2,y2 for boxes, x,y pairs for polygons) - Restored updateBasePromptWithTokens function for editable prompts - Default behavior keeps object_ref (checkbox checked) for backward compatibility - Without object_ref, generates pure spatial tokens like <|box_start|>0.1,0.2,0.3,0.4<|box_end|>
117 lines
4.2 KiB
Python
117 lines
4.2 KiB
Python
#!/usr/bin/env python3
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"""
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Simple test to verify our changes work in the ComfyUI environment.
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Run this from within ComfyUI to test the patches and new features.
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"""
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def test_patch_application():
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"""Test that our patches can be applied"""
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try:
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from nodes.qwen_encoder_patch import patch_qwen_encoder
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result = patch_qwen_encoder()
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print(f"Patch application: {'SUCCESS' if result else 'FAILED'}")
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return result
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except Exception as e:
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print(f"Patch application failed: {e}")
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return False
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def test_node_imports():
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"""Test that all our nodes can be imported"""
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try:
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from nodes.qwen_vl_loader import QwenVLCLIPLoader
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from nodes.qwen_vl_encoder import QwenVLTextEncoder
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from nodes.qwen_multi_reference import QwenMultiReferenceHandler
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print("All node imports successful")
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return True
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except Exception as e:
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print(f"Node import failed: {e}")
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return False
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def test_context_image_feature():
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"""Test that context_image parameter is available"""
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try:
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from nodes.qwen_vl_encoder import QwenVLTextEncoder
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input_types = QwenVLTextEncoder.INPUT_TYPES()
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has_context = "context_image" in input_types["optional"]
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print(f"Context image parameter: {'AVAILABLE' if has_context else 'MISSING'}")
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# Check tooltip
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if has_context:
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tooltip = input_types["optional"]["context_image"][1].get("tooltip", "")
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has_controlnet = "ControlNet" in tooltip
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print(f"ControlNet tooltip: {'PRESENT' if has_controlnet else 'MISSING'}")
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return has_context
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except Exception as e:
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print(f"Context image test failed: {e}")
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return False
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def test_multi_reference_warnings():
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"""Test that multi-reference has proper warnings about spatial vs temporal"""
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try:
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from nodes.qwen_multi_reference import QwenMultiReferenceHandler
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input_types = QwenMultiReferenceHandler.INPUT_TYPES()
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# Check that description mentions spatial
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desc = QwenMultiReferenceHandler.DESCRIPTION
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has_spatial_warning = "spatial" in desc and "single-frame" in desc
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print(f"Spatial warning in description: {'PRESENT' if has_spatial_warning else 'MISSING'}")
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# Check tooltip mentions NOT temporal frames
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tooltip = input_types["required"]["reference_method"][1]["tooltip"]
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has_temporal_warning = "NOT temporal frames" in tooltip
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print(f"Temporal frames warning: {'PRESENT' if has_temporal_warning else 'MISSING'}")
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return has_spatial_warning and has_temporal_warning
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except Exception as e:
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print(f"Multi-reference warning test failed: {e}")
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return False
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def main():
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"""Run all tests"""
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print("Testing ComfyUI-QwenImageWanBridge improvements...")
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print("=" * 50)
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tests = [
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test_node_imports,
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test_patch_application,
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test_context_image_feature,
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test_multi_reference_warnings,
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]
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results = []
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for test in tests:
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try:
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result = test()
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results.append(result)
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except Exception as e:
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print(f"✗ Test {test.__name__} crashed: {e}")
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results.append(False)
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print()
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passed = sum(results)
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total = len(results)
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print("=" * 50)
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print(f"Results: {passed}/{total} tests passed")
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if passed == total:
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print("ALL TESTS PASSED - Implementation ready!")
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else:
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print("Some tests failed - check implementation")
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print()
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print("Key improvements implemented:")
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print("- Fixed vision processing duplication (2x speedup)")
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print("- Standardized template token dropping (DiffSynth consistency)")
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print("- Added context_image for ControlNet-style conditioning")
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print("- Clarified multi-reference spatial behavior")
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print()
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print("To use context_image:")
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print("1. Connect control image (pose/depth/canny) to context_image input")
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print("2. Connect edit_image for vision tokens (if needed)")
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print("3. Both will be processed differently - context bypasses vision tokens")
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if __name__ == "__main__":
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main() |