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ultralytics 8.2.49 fix classification setup_model (#14199)

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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2024-07-05 00:58:04 +08:00 • committed by GitHub
parent 6c13bea7b8
commit 64862f1b69
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2 changed files with 8 additions and 17 deletions
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2
ultralytics/__init__.py
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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.48"
__version__ = "8.2.49"
import os

23
ultralytics/models/yolo/classify/train.py
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@ -5,7 +5,7 @@ import torch
from ultralytics.data import ClassificationDataset, build_dataloader
from ultralytics.engine.trainer import BaseTrainer
from ultralytics.models import yolo
from ultralytics.nn.tasks import ClassificationModel, attempt_load_one_weight
from ultralytics.nn.tasks import ClassificationModel
from ultralytics.utils import DEFAULT_CFG, LOGGER, RANK, colorstr
from ultralytics.utils.plotting import plot_images, plot_results
from ultralytics.utils.torch_utils import is_parallel, strip_optimizer, torch_distributed_zero_first
@ -60,23 +60,14 @@ class ClassificationTrainer(BaseTrainer):
"""Load, create or download model for any task."""
import torchvision # scope for faster 'import ultralytics'
if isinstance(self.model, torch.nn.Module): # if model is loaded beforehand. No setup needed
return
model, ckpt = str(self.model), None
# Load a YOLO model locally, from torchvision, or from Ultralytics assets
if model.endswith(".pt"):
self.model, ckpt = attempt_load_one_weight(model, device="cpu")
for p in self.model.parameters():
p.requires_grad = True # for training
elif model.split(".")[-1] in {"yaml", "yml"}:
self.model = self.get_model(cfg=model)
elif model in torchvision.models.__dict__:
self.model = torchvision.models.__dict__[model](weights="IMAGENET1K_V1" if self.args.pretrained else None)
if str(self.model) in torchvision.models.__dict__:
self.model = torchvision.models.__dict__[self.model](
weights="IMAGENET1K_V1" if self.args.pretrained else None
)
ckpt = None
else:
raise FileNotFoundError(f"ERROR: model={model} not found locally or online. Please check model name.")
ckpt = super().setup_model()
ClassificationModel.reshape_outputs(self.model, self.data["nc"])
return ckpt
def build_dataset(self, img_path, mode="train", batch=None):