updates

detect.py

@@ -1,5 +1,6 @@
 import argparse
 import time
+from sys import platform
 
 from models import *
 from utils.datasets import *

models.py

@@ -243,7 +243,7 @@ class Darknet(nn.Module):
     def __init__(self, cfg_path, img_size=416):
         super(Darknet, self).__init__()
 
-        self.module_defs = parse_model_config(cfg_path)
+        self.module_defs = parse_model_cfg(cfg_path)
         self.module_defs[0]['cfg'] = cfg_path
         self.module_defs[0]['height'] = img_size
         self.hyperparams, self.module_list = create_modules(self.module_defs)

utils/datasets.py

@@ -2,7 +2,6 @@ import glob
 import math
 import os
 import random
-from sys import platform
 
 import cv2
 import numpy as np

utils/parse_config.py

@@ -1,4 +1,4 @@
-def parse_model_config(path):
+def parse_model_cfg(path):
     """Parses the yolo-v3 layer configuration file and returns module definitions"""
     file = open(path, 'r')
     lines = file.read().split('\n')

utils/torch_utils.py

@@ -1,16 +1,9 @@
 import torch
 
 
-def check_cuda():
-    return torch.cuda.is_available()
-
-
-CUDA_AVAILABLE = check_cuda()
-
-
 def init_seeds(seed=0):
     torch.manual_seed(seed)
-    if CUDA_AVAILABLE:
+    if torch.cuda.is_available():
         torch.cuda.manual_seed(seed)
         torch.cuda.manual_seed_all(seed)
         # torch.cuda.set_device(0)  # OPTIONAL: Set your GPU if multiple available
@@ -20,6 +13,6 @@ def select_device(force_cpu=False):
     if force_cpu:
         device = torch.device('cpu')
     else:
-        device = torch.device('cuda:0' if CUDA_AVAILABLE else 'cpu')
+        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
     print('Using ' + str(device) + '\n')
     return device