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ultralytics 8.0.12 - Hydra removal (#506)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Pronoy Mandal <lukex9442@gmail.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
This commit is contained in:
Glenn Jocher
2023-01-21 00:45:19 +01:00
committed by GitHub
parent 6eec39162a
commit c5fccc3fc4
37 changed files with 395 additions and 469 deletions
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6
ultralytics/yolo/v8/detect/predict.py
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@ -1,11 +1,10 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
import hydra
import torch
from ultralytics.yolo.engine.predictor import BasePredictor
from ultralytics.yolo.engine.results import Results
from ultralytics.yolo.utils import DEFAULT_CONFIG, ROOT, is_git_directory, ops
from ultralytics.yolo.utils import DEFAULT_CFG, ROOT, is_git_directory, ops
from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_box
@ -81,8 +80,7 @@ class DetectionPredictor(BasePredictor):
return log_string
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def predict(cfg):
def predict(cfg=DEFAULT_CFG):
cfg.model = cfg.model or "yolov8n.pt"
cfg.source = cfg.source if cfg.source is not None else ROOT / "assets" if is_git_directory() \
else "https://ultralytics.com/images/bus.jpg"

10
ultralytics/yolo/v8/detect/train.py
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@ -2,7 +2,6 @@
from copy import copy
import hydra
import torch
import torch.nn as nn
@ -11,7 +10,7 @@ from ultralytics.yolo import v8
from ultralytics.yolo.data import build_dataloader
from ultralytics.yolo.data.dataloaders.v5loader import create_dataloader
from ultralytics.yolo.engine.trainer import BaseTrainer
from ultralytics.yolo.utils import DEFAULT_CONFIG, colorstr
from ultralytics.yolo.utils import DEFAULT_CFG, colorstr
from ultralytics.yolo.utils.loss import BboxLoss
from ultralytics.yolo.utils.ops import xywh2xyxy
from ultralytics.yolo.utils.plotting import plot_images, plot_results
@ -30,7 +29,7 @@ class DetectionTrainer(BaseTrainer):
imgsz=self.args.imgsz,
batch_size=batch_size,
stride=gs,
hyp=dict(self.args),
hyp=vars(self.args),
augment=mode == "train",
cache=self.args.cache,
pad=0 if mode == "train" else 0.5,
@ -195,8 +194,7 @@ class Loss:
return loss.sum() * batch_size, loss.detach() # loss(box, cls, dfl)
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def train(cfg):
def train(cfg=DEFAULT_CFG):
cfg.model = cfg.model or "yolov8n.pt"
cfg.data = cfg.data or "coco128.yaml" # or yolo.ClassificationDataset("mnist")
cfg.device = cfg.device if cfg.device is not None else ''
@ -204,7 +202,7 @@ def train(cfg):
# trainer.train()
from ultralytics import YOLO
model = YOLO(cfg.model)
model.train(**cfg)
model.train(**vars(cfg))
if __name__ == "__main__":

8
ultralytics/yolo/v8/detect/val.py
View File

@ -3,14 +3,13 @@
import os
from pathlib import Path
import hydra
import numpy as np
import torch
from ultralytics.yolo.data import build_dataloader
from ultralytics.yolo.data.dataloaders.v5loader import create_dataloader
from ultralytics.yolo.engine.validator import BaseValidator
from ultralytics.yolo.utils import DEFAULT_CONFIG, colorstr, ops, yaml_load
from ultralytics.yolo.utils import DEFAULT_CFG, colorstr, ops, yaml_load
from ultralytics.yolo.utils.checks import check_file, check_requirements
from ultralytics.yolo.utils.metrics import ConfusionMatrix, DetMetrics, box_iou
from ultralytics.yolo.utils.plotting import output_to_target, plot_images
@ -168,7 +167,7 @@ class DetectionValidator(BaseValidator):
imgsz=self.args.imgsz,
batch_size=batch_size,
stride=gs,
hyp=dict(self.args),
hyp=vars(self.args),
cache=False,
pad=0.5,
rect=True,
@ -232,8 +231,7 @@ class DetectionValidator(BaseValidator):
return stats
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def val(cfg):
def val(cfg=DEFAULT_CFG):
cfg.model = cfg.model or "yolov8n.pt"
cfg.data = cfg.data or "coco128.yaml"
validator = DetectionValidator(args=cfg)