调整mask大小为1024*1024,且更换了rgb背景的模型

02_classification.ipynb

@@ -12,8 +12,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "outputs": [],
+   "execution_count": 1,
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\FEIJINTI\\miniconda3\\envs\\deepo\\lib\\site-packages\\tqdm\\auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training env\n"
+     ]
+    }
+   ],
    "source": [
     "import numpy as np\n",
     "import scipy\n",
@@ -30,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "outputs": [],
    "source": [
     "train_from_existed = False # 是否从现有数据训练，如果是的话，那就从dataset_file训练，否则就用data_dir里头的数据\n",
@@ -70,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "outputs": [],
    "source": [
     "dataset = read_labeled_img(data_dir, color_dict=color_dict, is_ps_color_space=False)\n",
@@ -99,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "outputs": [],
    "source": [
     "if len(dataset) > 1:\n",
@@ -130,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
    "outputs": [],
    "source": [
     "# 对数据进行预处理\n",
@@ -147,13 +163,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "31173it [01:21, 380.30it/s]                                                                         \n"
+      "147099it [31:23, 78.09it/s]                                                                         \n"
      ]
     },
     {
@@ -162,12 +178,12 @@
      "text": [
       "              precision    recall  f1-score   support\n",
       "\n",
-      "           0       1.00      1.00      1.00      9352\n",
-      "           1       1.00      1.00      1.00      7793\n",
+      "           0       1.00      1.00      1.00     44129\n",
+      "           1       1.00      1.00      1.00     36775\n",
       "\n",
-      "    accuracy                           1.00     17145\n",
-      "   macro avg       1.00      1.00      1.00     17145\n",
-      "weighted avg       1.00      1.00      1.00     17145\n",
+      "    accuracy                           1.00     80904\n",
+      "   macro avg       1.00      1.00      1.00     80904\n",
+      "weighted avg       1.00      1.00      1.00     80904\n",
       "\n"
      ]
     }

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
@@ -34,7 +34,7 @@ class Config:
     ai_conf_threshold = 0.5
 
     # mask parameter
-    target_size = (256, 1024)  # (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

models/__init__.py

@@ -21,7 +21,7 @@ from detector import SugarDetect
 from utils import lab_scatter, read_labeled_img, size_threshold
 
 
-deploy = True
+deploy = False
 if not deploy:
     print("Training env")
     from tqdm import tqdm