diff --git a/config.py b/config.py index 718bf17..1f4e295 100644 --- a/config.py +++ b/config.py @@ -26,7 +26,7 @@ class Config: # rgb模型参数 rgb_tobacco_model_path = r"weights/tobacco_dt_2022-08-05_10-38.model" - rgb_background_model_path = r"weights/background_dt_2022-08-09_16-08.model" + rgb_background_model_path = r"weights/background_dt_2022-08-22_22-15.model" threshold_low, threshold_high = 10, 230 threshold_s = 190 # 饱和度的最高允许值 rgb_size_threshold = 4 # rgb的尺寸限制 @@ -38,7 +38,7 @@ class Config: valve_merge_size = 2 # 每两个喷阀当中有任意一个出现杂质则认为都是杂质 valve_horizontal_padding = 3 # 喷阀横向膨胀的尺寸，应该是奇数,3时表示左右各膨胀1 max_open_valve_limit = 25 # 最大同时开启喷阀限制,按照电流计算，当前的喷阀可以开启的喷阀 600W的电源 / 12V电源 = 50A, 一个阀门1A - + max_time_spent = 200 # save part offset_vertical = 0 diff --git a/main.py b/main.py index 69e7bed..9937170 100755 --- a/main.py +++ b/main.py @@ -22,51 +22,58 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None, 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 single_color: + logging.info("create color fifo") 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 single_spec: + logging.info("create rgb fifo") if not os.access(rgb_fifo_path, os.F_OK): os.mkfifo(rgb_fifo_path, 0o777) if not os.access(rgb_mask_fifo_path, os.F_OK): os.mkfifo(rgb_mask_fifo_path, 0o777) logging.info(f"请注意!正在以调试模式运行程序，输出的信息可能较多。") + # specially designed for Miaow. if (interval_time is not None) and (delay_repeat_time is not None): interval_time = float(interval_time) / 1000.0 delay_repeat_time = int(delay_repeat_time) logging.warning(f'Delay {interval_time*1000:.2f}ms will be added per {delay_repeat_time} frames') delay_repeat_time_count = 0 while True: - if not single_color: + img_data, rgb_data = None, None + if single_spec: fd_img = os.open(img_fifo_path, os.O_RDONLY) # spec data read - data = os.read(fd_img, total_len) - if len(data) < 3: + data_total = os.read(fd_img, total_len) + if len(data_total) < 3: try: - threshold = int(float(data)) + threshold = int(float(data_total)) Config.spec_size_threshold = threshold logging.info(f'[INFO] Get spec threshold: {threshold}') except Exception as e: logging.error( - f'毁灭性错误:收到长度小于3却无法转化为整数spec_size_threshold的网络报文，报文内容为 {data},' + f'毁灭性错误:收到长度小于3却无法转化为整数spec_size_threshold的网络报文，报文内容为 {data_total},' f' 错误为 {e}.') + if single_spec: + continue else: - data_total = data + data_total = data_total os.close(fd_img) try: img_data = np.frombuffer(data_total, dtype=np.float32).reshape((Config.nRows, Config.nBands, -1)) \ .transpose(0, 2, 1) + print(f"get image_shape {img_data.shape}") except Exception as e: logging.error(f'毁灭性错误!收到的光谱数据长度为{len(data_total)}无法转化成指定的形状 {e}') - if not single_spec: + if single_color: fd_rgb = os.open(rgb_fifo_path, os.O_RDONLY) # rgb data read - rgb_data = os.read(fd_rgb, total_rgb) - if len(rgb_data) < 3: + rgb_data_total = os.read(fd_rgb, total_rgb) + if len(rgb_data_total) < 3: try: - rgb_threshold = int(float(rgb_data)) + rgb_threshold = int(float(rgb_data_total)) Config.rgb_size_threshold = rgb_threshold logging.info(f'Get rgb threshold: {rgb_threshold}') except Exception as e: @@ -74,23 +81,29 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None, f' 错误为 {e}.') continue else: - rgb_data_total = rgb_data + rgb_data_total = rgb_data_total os.close(fd_rgb) try: rgb_data = np.frombuffer(rgb_data_total, dtype=np.uint8).reshape((Config.nRgbRows, Config.nRgbCols, -1)) + print(f"get rgb_data shape {rgb_data.shape}") except Exception as e: - logging.error(f'毁灭性错误!收到的rgb数据长度为{len(rgb_data)}无法转化成指定形状 {e}') + logging.error(f'毁灭性错误!收到的rgb数据长度为{len(rgb_data_total)}无法转化成指定形状 {e}') # 识别 read since = time.time() # predict if single_spec or single_color: + print('start predict') if single_spec: + print('spec predict', img_data.shape) mask_spec = spec_detector.predict(img_data).astype(np.uint8) masks = [mask_spec, ] + print('spectral mask shape:', masks[0].shape) else: + print('rgb predict', rgb_data.shape) mask_rgb = rgb_detector.predict(rgb_data).astype(np.uint8) masks = [mask_rgb, ] + print("rgb mask shape: ", masks[0].shape) else: if only_spec: # 光谱识别 @@ -127,8 +140,10 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None, else: output_fifos = [mask_fifo_path, rgb_mask_fifo_path] for fifo, mask in zip(output_fifos, masks): + print("open fifo") fd_mask = os.open(fifo, os.O_WRONLY) os.write(fd_mask, mask.tobytes()) + print("close fifo") os.close(fd_mask) time_spent = (time.time() - since) * 1000 predict_by = 'spec' if single_spec else 'rgb' if single_color else 'spec+rgb' @@ -162,4 +177,5 @@ if __name__ == '__main__': console_handler.setLevel(logging.DEBUG if args.d else logging.WARNING) logging.basicConfig(format='%(asctime)s - %(levelname)s - %(message)s', handlers=[file_handler, console_handler], level=logging.DEBUG) - main(only_spec=args.os, only_color=args.oc, if_merge=args.m, interval_time=args.dt, delay_repeat_time=args.df) + main(only_spec=args.os, only_color=args.oc, if_merge=args.m, interval_time=args.dt, delay_repeat_time=args.df, + single_spec=args.ss, single_color=args.sc)