添加了单通道预测的功能

main.py

@@ -1,19 +1,13 @@
 import os
+import cv2
 import time
-from queue import Queue
-
 import numpy as np
-from matplotlib import pyplot as plt
-
-import models
-import transmit
 
 from config import Config
 from models import RgbDetector, SpecDetector
-import cv2
 
 
-def main():
+def main(only_spec=False, only_color=False):
     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)
@@ -25,17 +19,12 @@ def main():
         os.mkfifo(rgb_fifo_path, 0o777)
     if not os.access(mask_fifo_path, os.F_OK):
         os.mkfifo(mask_fifo_path, 0o777)
-
+    if not os.access(rgb_mask_fifo_path, os.F_OK):
-    # 进行补偿buffer的开启
+        os.mkfifo(rgb_mask_fifo_path, 0o777)
-    if Config.offset_vertical < 0:
-        # 纵向的补偿小于0，那就意味着光谱图要上移才能补上，那么我们应该补偿SPEC相机的全 0 图像
-        conserve_part = np.zeros((abs(Config.offset_vertical) // 4, Config.nRows, Config.nBands))
-    elif Config.offset_vertical > 0:
-        # 纵向的补偿小于0，说明光谱图下移才能补上去，那么我们就需要补偿RGB相机的全 0 图像
-        conserve_part = np.zeros(abs(Config.offset_vertical), Config.nRgbRows, Config.nRgbBands)
     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:
@@ -45,6 +34,7 @@ def main():
         else:
             data_total = data
         os.close(fd_img)
+
         # rgb data read
         rgb_data = os.read(fd_rgb, total_rgb)
         if len(rgb_data) < 3:
@@ -55,36 +45,28 @@ def main():
         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))
-
+        if only_spec:
-        # OFFSET compensate
-        if Config.offset_vertical < 0:
-            # 纵向的补偿小于0，那就意味着光谱图要上移才能补上，那么我们应该补偿SPEC相机的全 0 图像
-            new_conserve_part, real_part = img_data[:abs(Config.offset_vertical) // 4, ...],\
-                                       img_data[abs(Config.offset_vertical) // 4:, ...]
-            img_data = np.concatenate([real_part, conserve_part], axis=0)
-            conserve_part = new_conserve_part
-        elif Config.offset_vertical > 0:
-            # 纵向的补偿小于0，说明光谱图下移才能补上去，那么我们就需要补偿RGB相机的全 0 图像
-            new_conserve_part, real_part = rgb_data[:abs(Config.offset_vertical), ...],\
-                                           rgb_data[abs(Config.offset_vertical):, ...]
-            rgb_data = np.concatenate([real_part, conserve_part], axis=0)
-            conserve_part = new_conserve_part
             # 光谱识别
             mask_spec = spec_detector.predict(img_data)
+            mask_rgb = np.zeros_like(mask_spec, dtype=np.uint8)
+        elif only_color:
             # rgb识别
             mask_rgb = rgb_detector.predict(rgb_data)
-        # 结果合并
+            mask_spec = np.zeros_like(mask_rgb, dtype=np.uint8)
-        mask_result = (mask_spec | mask_rgb).astype(np.uint8)
+        else:
+            mask_spec = spec_detector.predict(img_data)
+            mask_rgb = rgb_detector.predict(rgb_data)
 
         # control the size of the output masks
-        masks = [cv2.resize(mask.astype(np.uint8), Config.target_size) for mask in [mask_result, ]]
+        masks = [cv2.resize(mask.astype(np.uint8), Config.target_size) for mask in [mask_spec, mask_rgb]]
         # 写出
-        output_fifos = [mask_fifo_path, ]
+        output_fifos = [mask_fifo_path, rgb_mask_fifo_path]
         for fifo, mask in zip(output_fifos, masks):
             fd_mask = os.open(fifo, os.O_WRONLY)
             os.write(fd_mask, mask.tobytes())
@@ -94,12 +76,15 @@ def main():
 
 
 if __name__ == '__main__':
-    # 相关参数
+    import argparse
+    parser = argparse.ArgumentParser(description='主程序')
+    parser.add_argument('-oc', default=False, action='store_true', help='只进行RGB彩色预测 only rgb', required=False)
+    parser.add_argument('-os', default=False, action='store_true', help='只进行光谱预测 only spec', required=False)
+    args = parser.parse_args()
+    # fifo 参数
     img_fifo_path = "/tmp/dkimg.fifo"
     rgb_fifo_path = "/tmp/dkrgb.fifo"
-
+    # mask fifo
     mask_fifo_path = "/tmp/dkmask.fifo"
-    # 主函数
+    rgb_mask_fifo_path = "/tmp/dkmask_rgb.fifo"
-    main()
+    main(only_spec=args.os, only_color=args.oc)
-    # read_c_captures('/home/lzy/2022.7.15/tobacco_v1_0/', no_mask=True, nrows=256, ncols=1024,
-    #                 selected_bands=[380, 300, 200])