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https://github.com/NanjingForestryUniversity/tobacoo-industry.git
synced 2025-11-08 14:23:53 +00:00
66 lines
2.1 KiB
Python
Executable File
66 lines
2.1 KiB
Python
Executable File
import os
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import time
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import cv2
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import numpy as np
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from models import SpecDetector, PixelWisedDetector
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from root_dir import ROOT_DIR
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nrows, ncols, nbands = 256, 1024, 4
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img_fifo_path = "/tmp/dkimg.fifo"
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mask_fifo_path = "/tmp/dkmask.fifo"
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selected_model = "rf_8x8_c4_185_sen32_4.model"
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pxl_model_path = "rf_1x1_c4_1_sen1_4.model"
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def main():
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model_path = os.path.join(ROOT_DIR, "models", selected_model)
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detector = SpecDetector(model_path, blk_sz=8, channel_num=4)
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model_path = os.path.join(ROOT_DIR, "models", pxl_model_path)
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detector2 = PixelWisedDetector(model_path, blk_sz=1, channel_num=4)
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_ = detector.predict(np.ones((nrows, ncols, nbands)))
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_ = detector2.predict(np.ones((nrows, ncols, nbands)))
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total_len = nrows * ncols * nbands * 4
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if not os.access(img_fifo_path, os.F_OK):
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os.mkfifo(img_fifo_path, 0o777)
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if not os.access(mask_fifo_path, os.F_OK):
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os.mkfifo(mask_fifo_path, 0o777)
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data = b''
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while True:
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# 读取
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fd_img = os.open(img_fifo_path, os.O_RDONLY)
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while len(data) < total_len:
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data += os.read(fd_img, total_len)
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if len(data) > total_len:
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data_total = data[:total_len]
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data = data[total_len:]
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else:
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data_total = data
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data = b''
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os.close(fd_img)
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# 识别
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img = np.frombuffer(data_total, dtype=np.float32).reshape((nrows, nbands, -1)).transpose(0, 2, 1)
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t1 = time.time()
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mask1 = detector.predict(img)
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t2 = time.time()
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mask2 = detector2.predict(img)
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t3 = time.time()
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mask = mask2 & mask1
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t4 = time.time()
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print("="*40)
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print(f"block: {(t2 - t1)*1000:.2f}ms \n,"
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f"pixel: {(t3 - t2)*1000:.2f}ms \n"
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f"mask: {(t4 -t3)*1000:.2f}ms \n"
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f"Total: {(t4 - t1)*1000:.2f}ms")
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print("="*40)
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print()
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# 写出
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fd_mask = os.open(mask_fifo_path, os.O_WRONLY)
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os.write(fd_mask, mask.tobytes())
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os.close(fd_mask)
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if __name__ == '__main__':
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main()
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