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Update/inplace ops (#5233) 

* Clip Objects365 autodownload labels (#5214)

Fixes out of bounds labels that seem to affect ~10% of images in dataset.

* Inplace ops
pull/5232/head
Glenn Jocher 2021-10-18 14:24:48 +02:00 committed by GitHub
parent 0000334a6f
commit 13f7275555
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 6 additions and 5 deletions
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7
data/Objects365.yaml
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@ -63,7 +63,7 @@ download: |
from pycocotools.coco import COCO from pycocotools.coco import COCO
from tqdm import tqdm from tqdm import tqdm
from utils.general import download, Path from utils.general import Path, download, np, xyxy2xywhn
# Make Directories # Make Directories
dir = Path(yaml['path']) # dataset root dir dir = Path(yaml['path']) # dataset root dir
@ -105,7 +105,8 @@ download: |
annIds = coco.getAnnIds(imgIds=im["id"], catIds=catIds, iscrowd=None) annIds = coco.getAnnIds(imgIds=im["id"], catIds=catIds, iscrowd=None)
for a in coco.loadAnns(annIds): for a in coco.loadAnns(annIds):
x, y, w, h = a['bbox'] # bounding box in xywh (xy top-left corner) x, y, w, h = a['bbox'] # bounding box in xywh (xy top-left corner)
x, y = x + w / 2, y + h / 2 # xy to center xyxy = np.array([x, y, x + w, y + h])[None] # pixels(1,4)
file.write(f"{cid} {x / width:.5f} {y / height:.5f} {w / width:.5f} {h / height:.5f}\n") x, y, w, h = xyxy2xywhn(xyxy, w=width, h=height, clip=True)[0] # normalized and clipped
file.write(f"{cid} {x:.5f} {y:.5f} {w:.5f} {h:.5f}\n")
except Exception as e: except Exception as e:
print(e) print(e)

2
detect.py
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@ -139,7 +139,7 @@ def run(weights=ROOT / 'yolov5s.pt', # model.pt path(s)
else: else:
img = torch.from_numpy(img).to(device) img = torch.from_numpy(img).to(device)
img = img.half() if half else img.float() # uint8 to fp16/32 img = img.half() if half else img.float() # uint8 to fp16/32
img = img / 255.0 # 0 - 255 to 0.0 - 1.0 img /= 255.0 # 0 - 255 to 0.0 - 1.0
if len(img.shape) == 3: if len(img.shape) == 3:
img = img[None] # expand for batch dim img = img[None] # expand for batch dim
t2 = time_sync() t2 = time_sync()

2
utils/loggers/wandb/wandb_utils.py
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@ -433,7 +433,7 @@ class WandbLogger():
"box_caption": "%s %.3f" % (names[cls], conf), "box_caption": "%s %.3f" % (names[cls], conf),
"scores": {"class_score": conf}, "scores": {"class_score": conf},
"domain": "pixel"}) "domain": "pixel"})
total_conf = total_conf + conf total_conf += conf
boxes = {"predictions": {"box_data": box_data, "class_labels": names}} # inference-space boxes = {"predictions": {"box_data": box_data, "class_labels": names}} # inference-space
id = self.val_table_path_map[Path(path).name] id = self.val_table_path_map[Path(path).name]
self.result_table.add_data(self.current_epoch, self.result_table.add_data(self.current_epoch,