mirror of
https://github.com/NanjingForestryUniversity/supermachine-tobacco.git
synced 2025-11-08 14:23:55 +00:00
91 lines
3.6 KiB
Python
91 lines
3.6 KiB
Python
import os
|
|
import time
|
|
import numpy as np
|
|
from config import Config
|
|
from models import ManualTree, AnonymousColorDetector
|
|
|
|
|
|
# 主函数
|
|
def main():
|
|
threshold = Config.threshold
|
|
rgb_threshold = Config.rgb_threshold
|
|
manual_tree = ManualTree(blk_model_path=Config.blk_model_path, pixel_model_path=Config.pixel_model_path)
|
|
tobacco_detector = AnonymousColorDetector(file_path=Config.rgb_tobacco_model_path)
|
|
background_detector = AnonymousColorDetector(file_path=Config.rgb_background_model_path)
|
|
|
|
total_len = Config.nRows * Config.nCols * Config.nBands * 4 # float型变量, 4个字节
|
|
total_rgb = Config.nrgbRows * Config.nrgbCols * Config.nrgbBands * 1 # int型变量
|
|
if not os.access(img_fifo_path, os.F_OK):
|
|
os.mkfifo(img_fifo_path, 0o777)
|
|
if not os.access(mask_fifo_path, os.F_OK):
|
|
os.mkfifo(mask_fifo_path, 0o777)
|
|
if not os.access(rgb_fifo_path, os.F_OK):
|
|
os.mkfifo(rgb_fifo_path, 0o777)
|
|
while True:
|
|
fd_img = os.open(img_fifo_path, os.O_RDONLY)
|
|
fd_rgb = os.open(rgb_fifo_path, os.O_RDONLY)
|
|
data = os.read(fd_img, total_len)
|
|
|
|
# 读取(开启一个管道)
|
|
if len(data) < 3:
|
|
threshold = int(float(data))
|
|
print("[INFO] Get threshold: ", threshold)
|
|
continue
|
|
else:
|
|
data_total = data
|
|
rgb_data = os.read(fd_rgb, total_rgb)
|
|
if len(rgb_data) < 3:
|
|
rgb_threshold = int(float(rgb_data))
|
|
print(rgb_threshold)
|
|
continue
|
|
else:
|
|
rgb_data_total = rgb_data
|
|
|
|
os.close(fd_img)
|
|
os.close(fd_rgb)
|
|
|
|
# 识别
|
|
t1 = time.time()
|
|
img_data = np.frombuffer(data_total, dtype=np.float32).reshape((Config.nRows, Config.nBands,
|
|
-1)).transpose(0, 2, 1)
|
|
rgb_data = np.frombuffer(rgb_data_total, dtype=np.uint8)
|
|
pixel_predict_result = manual_tree.pixel_predict_ml_dilation(data=img_data, iteration=1)
|
|
blk_predict_result = manual_tree.blk_predict(data=img_data)
|
|
rgb_data = tobacco_detector.pretreatment(rgb_data)
|
|
rgb_predict_result = 1 - (
|
|
background_detector.predict(rgb_data) | tobacco_detector.swell(tobacco_detector.predict(rgb_data)))
|
|
mask_rgb = rgb_predict_result.reshape(Config.nRows, Config.nCols // Config.blk_size, Config.blk_size) \
|
|
.sum(axis=2).reshape(Config.nRows // 4, Config.blk_size, Config.nCols // Config.blk_size) \
|
|
.sum(axis=1)
|
|
mask_rgb[mask_rgb <= rgb_threshold] = 0
|
|
mask_rgb[mask_rgb > rgb_threshold] = 1
|
|
|
|
mask = (pixel_predict_result & blk_predict_result).astype(np.uint8)
|
|
mask = mask.reshape(Config.nRows, Config.nCols // Config.blk_size, Config.blk_size) \
|
|
.sum(axis=2).reshape(Config.nRows // 4, Config.blk_size, Config.nCols // Config.blk_size) \
|
|
.sum(axis=1)
|
|
mask[mask <= threshold] = 0
|
|
mask[mask > threshold] = 1
|
|
mask_result = (mask | mask_rgb).astype(np.uint8)
|
|
mask_result = mask_result.repeat(Config.blk_size, axis=0).repeat(Config.blk_size, axis=1).astype(np.uint8)
|
|
t2 = time.time()
|
|
# print(f'shibie time is:{t2 - t1}')
|
|
print(f'rgb len = {len(rgb_data)}')
|
|
|
|
# 写出
|
|
fd_mask = os.open(mask_fifo_path, os.O_WRONLY)
|
|
os.write(fd_mask, mask_result.tobytes())
|
|
os.close(fd_mask)
|
|
t3 = time.time()
|
|
print(f'total time is:{t3 - t1}')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
# 相关参数
|
|
img_fifo_path = "/tmp/dkimg.fifo"
|
|
mask_fifo_path = "/tmp/dkmask.fifo"
|
|
rgb_fifo_path = "/tmp/dkrgb.fifo"
|
|
|
|
# 主函数
|
|
main()
|