#378 修复依赖

requirements-dev-ext.txt

@@ -1,2 +1,3 @@
 polib==1.2.0
-pyinstaller==6.1.0
+pyinstaller==6.1.0
+pip-tools==7.4.1

requirements-dev.txt

@@ -9,4 +9,5 @@ pydantic==1.10.14
 scipy==1.13.0
 numpy==1.26.4
 shapely==2.0.4
-pyclipper==1.3.0.post5
+pyclipper==1.3.0.post5
+pytz==2024.1

requirements-prod.txt

@@ -4,7 +4,6 @@
 #
 #    pip-compile --annotation-style=line --index-url=https://pypi.tuna.tsinghua.edu.cn/simple --output-file=requirements-prod.txt requirements-dev.txt
 #
---index-url https://pypi.tuna.tsinghua.edu.cn/simple
 
 anyio==4.4.0              # via httpx, starlette, watchfiles
 arrow==1.3.0              # via cookiecutter
@@ -61,6 +60,7 @@ python-dotenv==1.0.1      # via uvicorn
 python-multipart==0.0.9   # via fastapi
 python-slugify==8.0.4     # via cookiecutter
 pytweening==1.2.0         # via pyautogui
+pytz==2024.1              # via -r requirements-dev.txt
 pyyaml==6.0.1             # via cookiecutter, uvicorn
 qrcode==7.4.2             # via flet
 repath==0.9.0             # via flet-core

src/sr/performance_recorder.py

@@ -1,7 +1,6 @@
 import time
 import os
 import yaml
-import psutil
 
 from basic import os_utils
 from basic.log_utils import log
@@ -92,11 +91,6 @@ def save_performance_record():
     """
     path = os.path.join(os_utils.get_path_under_work_dir('.log'), 'performance.txt')
     data = {}
-    data['cpu_frequency'] = f"{psutil.cpu_freq().current}MHz"
-    data['cpu_count'] = psutil.cpu_count()
-    memory_info = psutil.virtual_memory()
-    data['memory_total'] = f"{memory_info.total / (1024.0 ** 3)} GB"
-    data['memory_used'] = f"{memory_info.used / (1024.0 ** 3)} GB"
     for k, v in recorder.record_map.items():
         data['time_%s' % k] = v.avg
 

src/sryolo/detector.py

@@ -1,14 +1,15 @@
-import os
 import time
-import urllib.request
-import zipfile
-from typing import Optional, List, Tuple
 
+import csv
 import cv2
 import numpy as np
 import onnxruntime as ort
-import pandas as pd
+import os
+import urllib.request
+import zipfile
 from cv2.typing import MatLike
+from typing import Optional, List, Tuple
+
 from basic.log_utils import log
 
 
@@ -191,14 +192,16 @@ def load_detect_classes(self, model_dir_path: str):
         :return:
         """
         csv_path = os.path.join(model_dir_path, 'labels.csv')
-        labels_df = pd.read_csv(csv_path, encoding='utf-8')
-        self.idx_2_class = {}
-        self.class_2_idx = {}
-        self.cate_2_idx = {}
-        for _, row in labels_df.iterrows():
-            self.idx_2_class[row['idx']] = DetectClass(row['idx'], row['label'], row['cate'])
-            self.class_2_idx[row['label']] = row['idx']
-            self.cate_2_idx[row['cate']] = row['idx']
+        with open(csv_path, mode='r', encoding='utf-8') as file:
+            csv_reader = csv.reader(file)
+            for row in csv_reader:
+                if row[0] != 'idx':
+                    idx = int(row[0])
+                    label = row[1]
+                    cate = row[2]
+                    self.idx_2_class[idx] = DetectClass(idx, label, cate)
+                    self.class_2_idx[label] =idx
+                    self.cate_2_idx[cate] =idx
 
     def detect(self, image: MatLike,
                conf: float = 0.7,