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Add CoreML iOS updates (#121)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
This commit is contained in:
Glenn Jocher
2022-12-30 21:33:43 +01:00
committed by GitHub
parent fec13ec773
commit c9f3e469cb
13 changed files with 215 additions and 91 deletions
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7
ultralytics/yolo/v8/classify/predict.py
View File

@ -3,6 +3,7 @@ import torch
from ultralytics.yolo.engine.predictor import BasePredictor
from ultralytics.yolo.utils import DEFAULT_CONFIG
from ultralytics.yolo.utils.checks import check_imgsz
from ultralytics.yolo.utils.plotting import Annotator
@ -54,11 +55,7 @@ class ClassificationPredictor(BasePredictor):
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def predict(cfg):
cfg.model = cfg.model or "squeezenet1_0"
sz = cfg.imgsz
if type(sz) != int: # received listConfig
cfg.imgsz = [sz[0], sz[0]] if len(cfg.imgsz) == 1 else [sz[0], sz[1]] # expand
else:
cfg.imgsz = [sz, sz]
cfg.imgsz = check_imgsz(cfg.imgsz, min_dim=2) # check image size
predictor = ClassificationPredictor(cfg)
predictor()

7
ultralytics/yolo/v8/detect/predict.py
View File

@ -3,6 +3,7 @@ import torch
from ultralytics.yolo.engine.predictor import BasePredictor
from ultralytics.yolo.utils import DEFAULT_CONFIG, ops
from ultralytics.yolo.utils.checks import check_imgsz
from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_box
@ -83,11 +84,7 @@ class DetectionPredictor(BasePredictor):
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def predict(cfg):
cfg.model = cfg.model or "n.pt"
sz = cfg.imgsz
if type(sz) != int: # received listConfig
cfg.imgsz = [sz[0], sz[0]] if len(cfg.imgsz) == 1 else [sz[0], sz[1]] # expand
else:
cfg.imgsz = [sz, sz]
cfg.imgsz = check_imgsz(cfg.imgsz, min_dim=2) # check image size
predictor = DetectionPredictor(cfg)
predictor()

7
ultralytics/yolo/v8/segment/predict.py
View File

@ -2,6 +2,7 @@ import hydra
import torch
from ultralytics.yolo.utils import DEFAULT_CONFIG, ops
from ultralytics.yolo.utils.checks import check_imgsz
from ultralytics.yolo.utils.plotting import colors, save_one_box
from ..detect.predict import DetectionPredictor
@ -96,11 +97,7 @@ class SegmentationPredictor(DetectionPredictor):
@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
def predict(cfg):
cfg.model = cfg.model or "n.pt"
sz = cfg.imgsz
if type(sz) != int: # received listConfig
cfg.imgsz = [sz[0], sz[0]] if len(cfg.imgsz) == 1 else [sz[0], sz[1]] # expand
else:
cfg.imgsz = [sz, sz]
cfg.imgsz = check_imgsz(cfg.imgsz, min_dim=2) # check image size
predictor = SegmentationPredictor(cfg)
predictor()