🐛 Bug Got list index out of range ERROR when using results.print() To Reproduce (REQUIRED) Input: import torch from PIL import Image import numpy as np image_path = 'zidane.jpg' # or file, Path, PIL, OpenCV, numpy, list image = Image.ope...
y_true = [Input(shape=(h//{0:32, 1:16}[l], w//{0:32, 1:16}[l], \ num_anchors//2, num_classes+5)) for l in range(2)] model_body = tiny_yolo_body(image_input, num_anchors//2, num_classes) print('Create Tiny YOLOv3 model with {} anchors and {} classes.'.format(...
: 16%|▏| Traceback (most recent call last): File "train.py", line 632, in <module> main(opt) File "train.py", line 529, in main train(opt.hyp, opt, device, callbacks) File "train.py", line 336, in train GPU = GPUtil.getGPUs()[0] IndexError: list index out of range ...
tv = int(num * trainval_percent) tr = int(tv * train_percent) trainval = random.sample(list_index, tv) train = random.sample(trainval, tr) file_trainval = open(txtsavepath + '/trainval.txt', 'w') file_test = open(txtsavepath + '/test.txt', 'w') file_train = open(txts...
list_index = range(num) tv = int(num * trainval_percent) tr = int(tv * train_percent) trainval = random.sample(list_index, tv) train = random.sample(trainval, tr) file_trainval = open(txtsavepath + '/trainval.txt', 'w') ...
list_index = range(num) tv = int(num * trainval_percent) tr = int(tv * train_percent) trainval = random.sample(list_index, tv) train = random.sample(trainval, tr) file_trainval = open(txtsavepath +'trainval.txt','w')
append([ch[x] for x in f]) if isinstance(args[1], int): # number of anchors 几乎不执行 args[1] = [list(range(args[1] * 2))] * len(f) elif m is Contract: # 不怎么用 c2 = ch[f] * args[0] ** 2 elif m is Expand: # 不怎么用 c2 = ch[f] // args[0] ** 2 ...
执行后可以执行pip list命令查看当前环境下的所有模块,如果看到环境中有刚才安装的的模块,则环境已经配置完毕! 三、YOLOv5 实现训练 3.1 准备工作 首先从github上下载下来YOLOv5,楼主这里改名为yolov5-master-cat,因为是识别小猫猫的。然后在data目录下新建Annotations, images, ImageSets, labels 四个文件夹。
+ output = [np.array(all_list[i]).reshape(-1, 6) for i in range(batch_size)]+ # outputs = [torch.FloatTensor(all_list[i]).reshape(-1, 6) for i in range(batch_size)]+ return output+ # jdict = []+ # for si, pred in enumerate(output):...
list_index = range(num) tv = int(num * trainval_percent) tr = int(tv * train_percent) trainval = random.sample(list_index, tv) train = random.sample(trainval, tr) file_trainval = open(txtsavepath + '/trainval.txt', 'w') ...