charlie880624
ac3c30a1d2
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74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
import os
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import cv2
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import numpy as np
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import pandas as pd
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from pathlib import Path
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from tqdm import tqdm
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# ✅ 設定資料夾
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datasets = [
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{
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"name": "train",
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"input_dir": r"C:\Users\rd_de\kneronstdc\data\0507stdcgrass\train",
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"output_img_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\leftImg8bit\train",
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"output_mask_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\gtFine\train",
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},
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{
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"name": "val",
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"input_dir": r"C:\Users\rd_de\kneronstdc\data\0507stdcgrass\valid",
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"output_img_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\leftImg8bit\val",
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"output_mask_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\gtFine\val",
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},
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{
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"name": "test",
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"input_dir": r"C:\Users\rd_de\kneronstdc\data\0507stdcgrass\test",
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"output_img_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\leftImg8bit\test",
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"output_mask_dir": r"C:\Users\rd_de\kneronstdc\data\cityscapes\gtFine\test",
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}
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]
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# ✅ 只保留 grass: label 1 → 0，其餘變成 ignore (255)
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for dataset in datasets:
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name = dataset["name"]
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input_dir = dataset["input_dir"]
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output_img_dir = dataset["output_img_dir"]
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output_mask_dir = dataset["output_mask_dir"]
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os.makedirs(output_img_dir, exist_ok=True)
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os.makedirs(output_mask_dir, exist_ok=True)
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print(f"\n📂 資料集: {name}")
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for file in tqdm(os.listdir(input_dir), desc=f"轉換 {name}"):
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if not file.endswith("_mask.png"):
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continue
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mask_path = os.path.join(input_dir, file)
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image_name = file.replace("_mask.png", ".jpg")
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image_path = os.path.join(input_dir, image_name)
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if not os.path.exists(image_path):
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print(f"⚠️ 找不到對應圖片: {image_name}")
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continue
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img = cv2.imread(image_path)
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mask = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)
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if img is None or mask is None:
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print(f"❌ 無法讀取圖像或 mask: {file}")
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continue
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# ✅ 將草地 (1) → 0，其餘設為 ignore (255)
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remapped_mask = np.full_like(mask, 255, dtype=np.uint8)
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remapped_mask[mask == 1] = 0
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# ✅ 輸出
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stem = Path(file).stem.replace("_mask", "")
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out_img_path = os.path.join(output_img_dir, f"{stem}_leftImg8bit.png")
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out_mask_path = os.path.join(output_mask_dir, f"{stem}_gtFine_labelIds.png")
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cv2.imwrite(out_img_path, img)
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cv2.imwrite(out_mask_path, remapped_mask)
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print("\n🎉 轉換完成，只保留 grass 類別（label=0）！")
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