Unverified 提交 cff92634 authored 作者: Glenn Jocher's avatar Glenn Jocher 提交者: GitHub

f.read().strip() (#1551)

上级 9fa7f9f5
...@@ -450,7 +450,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing ...@@ -450,7 +450,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
if os.path.isfile(lb_file): if os.path.isfile(lb_file):
nf += 1 # label found nf += 1 # label found
with open(lb_file, 'r') as f: with open(lb_file, 'r') as f:
l = np.array([x.split() for x in f.read().splitlines()], dtype=np.float32) # labels l = np.array([x.split() for x in f.read().strip().splitlines()], dtype=np.float32) # labels
if len(l): if len(l):
assert l.shape[1] == 5, 'labels require 5 columns each' assert l.shape[1] == 5, 'labels require 5 columns each'
assert (l >= 0).all(), 'negative labels' assert (l >= 0).all(), 'negative labels'
...@@ -897,7 +897,7 @@ def extract_boxes(path='../coco128/'): # from utils.datasets import *; extract_ ...@@ -897,7 +897,7 @@ def extract_boxes(path='../coco128/'): # from utils.datasets import *; extract_
lb_file = Path(img2label_paths([str(im_file)])[0]) lb_file = Path(img2label_paths([str(im_file)])[0])
if Path(lb_file).exists(): if Path(lb_file).exists():
with open(lb_file, 'r') as f: with open(lb_file, 'r') as f:
lb = np.array([x.split() for x in f.read().splitlines()], dtype=np.float32) # labels lb = np.array([x.split() for x in f.read().strip().splitlines()], dtype=np.float32) # labels
for j, x in enumerate(lb): for j, x in enumerate(lb):
c = int(x[0]) # class c = int(x[0]) # class
......
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