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ultralytics 8.1.43 40% faster ultralytics imports (#9547)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-04-05 15:29:09 +02:00 • committed by GitHub
parent 99c61d6f7b
commit a2628657a1
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21 changed files with 240 additions and 225 deletions
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tests/test_python.py
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@ -10,7 +10,6 @@ import pytest
import torch
import yaml
from PIL import Image
from torchvision.transforms import ToTensor
from ultralytics import RTDETR, YOLO
from ultralytics.cfg import TASK2DATA
@ -108,20 +107,17 @@ def test_predict_img():
assert len(model(batch, imgsz=32)) == len(batch) # multiple sources in a batch
# Test tensor inference
im = cv2.imread(str(SOURCE)) # OpenCV
t = cv2.resize(im, (32, 32))
t = ToTensor()(t)
t = torch.stack([t, t, t, t])
results = model(t, imgsz=32)
assert len(results) == t.shape[0]
results = seg_model(t, imgsz=32)
assert len(results) == t.shape[0]
results = cls_model(t, imgsz=32)
assert len(results) == t.shape[0]
results = pose_model(t, imgsz=32)
assert len(results) == t.shape[0]
results = obb_model(t, imgsz=32)
assert len(results) == t.shape[0]
im = torch.rand((4, 3, 32, 32)) # batch-size 4, FP32 0.0-1.0 RGB order
results = model(im, imgsz=32)
assert len(results) == im.shape[0]
results = seg_model(im, imgsz=32)
assert len(results) == im.shape[0]
results = cls_model(im, imgsz=32)
assert len(results) == im.shape[0]
results = pose_model(im, imgsz=32)
assert len(results) == im.shape[0]
results = obb_model(im, imgsz=32)
assert len(results) == im.shape[0]
def test_predict_grey_and_4ch():
@ -592,8 +588,6 @@ def image():
)
def test_classify_transforms_train(image, auto_augment, erasing, force_color_jitter):
"""Tests classification transforms during training with various augmentation settings."""
import torchvision.transforms as T
from ultralytics.data.augment import classify_augmentations
transform = classify_augmentations(
@ -610,7 +604,6 @@ def test_classify_transforms_train(image, auto_augment, erasing, force_color_jit
hsv_v=0.4,
force_color_jitter=force_color_jitter,
erasing=erasing,
interpolation=T.InterpolationMode.BILINEAR,
)
transformed_image = transform(Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)))