supermachine-tobacco/main.py
2022-07-27 17:44:21 +08:00

104 lines
3.8 KiB
Python
Executable File

import os
import time
import matplotlib.pyplot as plt
import numpy as np
import scipy.io
from config import Config
from models import RgbDetector, SpecDetector, ManualTree, AnonymousColorDetector
import cv2
def main():
spec_detector = SpecDetector(blk_model_path=Config.blk_model_path, pixel_model_path=Config.pixel_model_path)
rgb_detector = RgbDetector(tobacco_model_path=Config.rgb_tobacco_model_path,
background_model_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)
# spec data read
data = os.read(fd_img, total_len)
if len(data) < 3:
threshold = int(float(data))
Config.spec_size_threshold = threshold
print("[INFO] Get spec threshold: ", threshold)
else:
data_total = data
os.close(fd_img)
# rgb data read
rgb_data = os.read(fd_rgb, total_rgb)
if len(rgb_data) < 3:
rgb_threshold = int(float(rgb_data))
Config.rgb_size_threshold = rgb_threshold
print("[INFO] Get rgb threshold", rgb_threshold)
continue
else:
rgb_data_total = rgb_data
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).reshape((Config.nRgbRows, Config.nRgbCols, -1))
# 光谱识别
mask = spec_detector.predict(img_data)
# rgb识别
mask_rgb = rgb_detector.predict(rgb_data)
# 结果合并
mask_result = (mask | mask_rgb).astype(np.uint8)
# mask_result = 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()
# 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}\n')
def read_c_captures(buffer_path):
buffer_names = [buffer_name for buffer_name in os.listdir(buffer_path) if buffer_name.endswith('.raw')]
for buffer_name in buffer_names:
with open(os.path.join(buffer_path, buffer_name), 'rb') as f:
data = f.read()
img = np.frombuffer(data, dtype=np.float32).reshape((Config.nRows, Config.nBands, -1)) \
.transpose(0, 2, 1)
mask_name = buffer_name.replace('buf', 'mask').replace('.raw', '')
with open(os.path.join(buffer_path, mask_name), 'rb') as f:
data = f.read()
mask = np.frombuffer(data, dtype=np.uint8).reshape((256, 1024, -1))
# mask = cv2.resize(mask, (1024, 256))
fig, axs = plt.subplots(2, 1)
axs[0].imshow(img[..., [21, 3, 0]])
axs[0].set_title(buffer_name)
axs[1].imshow(mask)
axs[1].set_title(mask_name)
plt.show()
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()
# read_c_captures('/home/lzy/2022.7.20/tobacco_v1_0/')