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- Add golf1/2/4/7/8 dataset classes for semantic segmentation - Add kneron-specific configs (meconfig series, kn_stdc1_golf4class) - Organize scripts into tools/check/ and tools/kneron/ - Add kneron_preprocessing module - Update README with quick-start guide - Update .gitignore to exclude data dirs, onnx, nef outputs Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
25 lines
802 B
Python
25 lines
802 B
Python
import onnxruntime as ort
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import numpy as np
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# ✅ 模型路徑（你指定的）
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onnx_path = r"C:\Users\rd_de\kneron-mmsegmentation\work_dirs\kn_stdc1_in1k-pre_512x1024_80k_cityscapes\latest.onnx"
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# 建立 ONNX session
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session = ort.InferenceSession(onnx_path)
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# 印出模型 input 相關資訊
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input_name = session.get_inputs()[0].name
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input_shape = session.get_inputs()[0].shape
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print(f"✅ Input name: {input_name}")
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print(f"✅ Input shape: {input_shape}")
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# 建立假圖輸入 (float32, shape = [1, 3, 512, 1024])
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dummy_input = np.random.rand(1, 3, 512, 1024).astype(np.float32)
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# 執行推論
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outputs = session.run(None, {input_name: dummy_input})
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# 顯示模型輸出資訊
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for i, output in enumerate(outputs):
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print(f"✅ Output {i}: shape = {output.shape}, dtype = {output.dtype}")
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