From 3a71daf4bc2ecbb14c26842714f404dbed15fb24 Mon Sep 17 00:00:00 2001 From: orcund <50711354+orcund@users.noreply.github.com> Date: Sat, 16 May 2020 21:09:57 +0300 Subject: [PATCH] Pseudo Labeling (#1149) * Added pseudo labeling * Delete print_test.py * Refactor label generation * Update detect.py * Update detect.py * Update utils.py Co-authored-by: Glenn Jocher --- detect.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/detect.py b/detect.py index 15582a5d..d655e63d 100644 --- a/detect.py +++ b/detect.py @@ -102,7 +102,7 @@ def detect(save_img=False): pred = apply_classifier(pred, modelc, img, im0s) # Process detections - for i, det in enumerate(pred): # detections per image + for i, det in enumerate(pred): # detections for image i if webcam: # batch_size >= 1 p, s, im0 = path[i], '%g: ' % i, im0s[i] else: @@ -110,6 +110,7 @@ def detect(save_img=False): save_path = str(Path(out) / Path(p).name) s += '%gx%g ' % img.shape[2:] # print string + gn = torch.tensor(im0s.shape)[[1, 0, 1, 0]] #  normalization gain whwh if det is not None and len(det): # Rescale boxes from img_size to im0 size det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round() @@ -122,8 +123,9 @@ def detect(save_img=False): # Write results for *xyxy, conf, cls in det: if save_txt: # Write to file + xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist() # normalized xywh with open(save_path + '.txt', 'a') as file: - file.write(('%g ' * 6 + '\n') % (*xyxy, cls, conf)) + file.write(('%g ' * 5 + '\n') % (cls, *xywh)) # label format if save_img or view_img: # Add bbox to image label = '%s %.2f' % (names[int(cls)], conf)