From 127e57eca541997012ca67863b4a63f48db1ff48 Mon Sep 17 00:00:00 2001
From: "li.zhenye" <li.zhenye@qq.com>
Date: Wed, 24 Aug 2022 09:39:44 +0800
Subject: [PATCH] perfect yolo version

---
 config.py   | 2 +-
 main.py     | 9 ---------
 transmit.py | 2 --
 3 files changed, 1 insertion(+), 12 deletions(-)

diff --git a/config.py b/config.py
index 1f4e295..1d88d64 100644
--- a/config.py
+++ b/config.py
@@ -34,7 +34,7 @@ class Config:
     ai_conf_threshold = 0.5
 
     # mask parameter
-    target_size = (256, 256)  # (Width, Height) of mask
+    target_size = (1024, 1024)  # (Width, Height) of mask
     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
diff --git a/main.py b/main.py
index 9937170..4771e10 100755
--- a/main.py
+++ b/main.py
@@ -63,7 +63,6 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None,
             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}')
 
@@ -85,7 +84,6 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None,
             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_total)}无法转化成指定形状 {e}')
 
@@ -93,17 +91,12 @@ def main(only_spec=False, only_color=False, if_merge=False, interval_time=None,
         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
@@ -140,10 +133,8 @@ 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'
diff --git a/transmit.py b/transmit.py
index 17e91e4..821385e 100644
--- a/transmit.py
+++ b/transmit.py
@@ -9,8 +9,6 @@ from config import Config
 from models import SpecDetector, RgbDetector
 import typing
 import logging
-logging.basicConfig(format='%(asctime)s %(levelname)s %(name)s %(message)s',
-                    level=logging.WARNING)
 
 
 class Transmitter(object):