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ultralytics 8.1.39 add YOLO-World training (#9268)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2024-03-31 22:30:17 +08:00 • committed by GitHub
parent 18036908d4
commit e9187c1296
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34 changed files with 2166 additions and 100 deletions
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53
ultralytics/models/yolo/detect/val.py
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@ -33,6 +33,7 @@ class DetectionValidator(BaseValidator):
super().__init__(dataloader, save_dir, pbar, args, _callbacks)
self.nt_per_class = None
self.is_coco = False
self.is_lvis = False
self.class_map = None
self.args.task = "detect"
self.metrics = DetMetrics(save_dir=self.save_dir, on_plot=self.on_plot)
@ -66,8 +67,9 @@ class DetectionValidator(BaseValidator):
"""Initialize evaluation metrics for YOLO."""
val = self.data.get(self.args.split, "") # validation path
self.is_coco = isinstance(val, str) and "coco" in val and val.endswith(f"{os.sep}val2017.txt") # is COCO
self.class_map = converter.coco80_to_coco91_class() if self.is_coco else list(range(1000))
self.args.save_json |= self.is_coco and not self.training # run on final val if training COCO
self.is_lvis = isinstance(val, str) and "lvis" in val and not self.is_coco # is LVIS
self.class_map = converter.coco80_to_coco91_class() if self.is_coco else list(range(len(model.names)))
self.args.save_json |= (self.is_coco or self.is_lvis) and not self.training # run on final val if training COCO
self.names = model.names
self.nc = len(model.names)
self.metrics.names = self.names
@ -266,7 +268,8 @@ class DetectionValidator(BaseValidator):
self.jdict.append(
{
"image_id": image_id,
"category_id": self.class_map[int(p[5])],
"category_id": self.class_map[int(p[5])]
+ (1 if self.is_lvis else 0), # index starts from 1 if it's lvis
"bbox": [round(x, 3) for x in b],
"score": round(p[4], 5),
}
@ -274,26 +277,42 @@ class DetectionValidator(BaseValidator):
def eval_json(self, stats):
"""Evaluates YOLO output in JSON format and returns performance statistics."""
if self.args.save_json and self.is_coco and len(self.jdict):
anno_json = self.data["path"] / "annotations/instances_val2017.json" # annotations
if self.args.save_json and (self.is_coco or self.is_lvis) and len(self.jdict):
pred_json = self.save_dir / "predictions.json" # predictions
LOGGER.info(f"\nEvaluating pycocotools mAP using {pred_json} and {anno_json}...")
anno_json = (
self.data["path"]
/ "annotations"
/ ("instances_val2017.json" if self.is_coco else f"lvis_v1_{self.args.split}.json")
) # annotations
pkg = "pycocotools" if self.is_coco else "lvis"
LOGGER.info(f"\nEvaluating {pkg} mAP using {pred_json} and {anno_json}...")
try: # https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocoEvalDemo.ipynb
check_requirements("pycocotools>=2.0.6")
from pycocotools.coco import COCO # noqa
from pycocotools.cocoeval import COCOeval # noqa
for x in anno_json, pred_json:
for x in pred_json, anno_json:
assert x.is_file(), f"{x} file not found"
anno = COCO(str(anno_json)) # init annotations api
pred = anno.loadRes(str(pred_json)) # init predictions api (must pass string, not Path)
eval = COCOeval(anno, pred, "bbox")
check_requirements("pycocotools>=2.0.6" if self.is_coco else "lvis>=0.5.3")
if self.is_coco:
eval.params.imgIds = [int(Path(x).stem) for x in self.dataloader.dataset.im_files] # images to eval
from pycocotools.coco import COCO # noqa
from pycocotools.cocoeval import COCOeval # noqa
anno = COCO(str(anno_json)) # init annotations api
pred = anno.loadRes(str(pred_json)) # init predictions api (must pass string, not Path)
eval = COCOeval(anno, pred, "bbox")
else:
from lvis import LVIS, LVISEval
anno = LVIS(str(anno_json)) # init annotations api
pred = anno._load_json(str(pred_json)) # init predictions api (must pass string, not Path)
eval = LVISEval(anno, pred, "bbox")
eval.params.imgIds = [int(Path(x).stem) for x in self.dataloader.dataset.im_files] # images to eval
eval.evaluate()
eval.accumulate()
eval.summarize()
stats[self.metrics.keys[-1]], stats[self.metrics.keys[-2]] = eval.stats[:2] # update mAP50-95 and mAP50
if self.is_lvis:
eval.print_results() # explicitly call print_results
# update mAP50-95 and mAP50
stats[self.metrics.keys[-1]], stats[self.metrics.keys[-2]] = (
eval.stats[:2] if self.is_coco else [eval.results["AP50"], eval.results["AP"]]
)
except Exception as e:
LOGGER.warning(f"pycocotools unable to run: {e}")
LOGGER.warning(f"{pkg} unable to run: {e}")
return stats