charlie880624
7716a0060f
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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>
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import os
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import numpy as np
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import onnx
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import shutil
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import cv2
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import ktc
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onnx_dir = 'work_dirs/kn_stdc1_in1k-pre_512x1024_80k_cityscapes/'
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onnx_path = os.path.join(onnx_dir, 'latest.onnx')
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data_path = "data512"
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imgsz = (512, 512)
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os.makedirs(onnx_dir, exist_ok=True)
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print("🔄 Loading and optimizing ONNX...")
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model = onnx.load(onnx_path)
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model = ktc.onnx_optimizer.onnx2onnx_flow(model)
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opt_onnx_path = os.path.join(onnx_dir, 'latest.opt.onnx')
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onnx.save(model, opt_onnx_path)
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print("📐 Configuring model...")
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km = ktc.ModelConfig(20008, "0001", "630", onnx_model=model)
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# Optional: performance check
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print("\n📊 Evaluating model...")
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print(km.evaluate())
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input_name = model.graph.input[0].name
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print("📥 ONNX input name:", input_name)
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img_list = []
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print("🖼️ Preprocessing images...")
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for root, _, files in os.walk(data_path):
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for fname in files:
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if fname.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp')):
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path = os.path.join(root, fname)
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img = cv2.imread(path)
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img = cv2.resize(img, imgsz)
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img = img.astype(np.float32) / 256.0 - 0.5
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img = np.transpose(img, (2, 0, 1)) # HWC ➝ CHW
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img = np.expand_dims(img, axis=0) # Add batch dim
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img_list.append(img)
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print("✅", path)
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if not img_list:
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raise RuntimeError("❌ No images processed!")
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print("📦 Quantizing (BIE)...")
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bie_path = km.analysis({input_name: img_list})
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bie_save = os.path.join(onnx_dir, os.path.basename(bie_path))
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shutil.copy(bie_path, bie_save)
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if not os.path.exists(bie_save):
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raise RuntimeError("❌ BIE model not saved!")
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print("⚙️ Compiling NEF...")
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nef_path = ktc.compile([km])
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nef_save = os.path.join(onnx_dir, os.path.basename(nef_path))
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shutil.copy(nef_path, nef_save)
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if not os.path.exists(nef_save):
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raise RuntimeError("❌ NEF model not saved!")
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print("✅ Compile finished. NEF at:", nef_save)
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