From cf54fa74684bd6ee7d369971ae938474d469e3aa Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Thu, 25 Apr 2019 22:47:31 +0200 Subject: [PATCH] updates --- utils/datasets.py | 4 +++- utils/utils.py | 11 ++++++----- 2 files changed, 9 insertions(+), 6 deletions(-) diff --git a/utils/datasets.py b/utils/datasets.py index eef26b9f..c1b31817 100755 --- a/utils/datasets.py +++ b/utils/datasets.py @@ -236,7 +236,9 @@ class LoadImagesAndLabels(Dataset): # for training/testing nL = len(labels) # number of labels if nL: # convert xyxy to xywh - labels[:, 1:5] = xyxy2xywh(labels[:, 1:5]) / self.img_size + labels[:, 1:5] = xyxy2xywh(labels[:, 1:5]) + labels[:, [2, 4]] /= img.shape[0] # height + labels[:, [1, 3]] /= img.shape[1] # width if self.augment: # random left-right flip diff --git a/utils/utils.py b/utils/utils.py index 3e400ff7..2eb8fcb2 100755 --- a/utils/utils.py +++ b/utils/utils.py @@ -500,13 +500,14 @@ def plot_images(imgs, targets, fname='images.jpg'): targets = targets.cpu().numpy() fig = plt.figure(figsize=(10, 10)) - img_size = imgs.shape[3] - bs = imgs.shape[0] # batch size - sp = np.ceil(bs ** 0.5) # subplots + bs, _, h, w = imgs.shape # batch size, _, height, width + ns = np.ceil(bs ** 0.5) # number of subplots for i in range(bs): - boxes = xywh2xyxy(targets[targets[:, 0] == i, 2:6]).T * img_size - plt.subplot(sp, sp, i + 1).imshow(imgs[i].transpose(1, 2, 0)) + boxes = xywh2xyxy(targets[targets[:, 0] == i, 2:6]).T + boxes[[0, 2]] *= w + boxes[[1, 3]] *= h + plt.subplot(ns, ns, i + 1).imshow(imgs[i].transpose(1, 2, 0)) plt.plot(boxes[[0, 2, 2, 0, 0]], boxes[[1, 1, 3, 3, 1]], '.-') plt.axis('off') fig.tight_layout()