def test_resize_tensor():
from ml import cv
H, W, size = 720, 1280, 256
img = th.randn(3, H, W)
resized = cv.resize(img, size)
h, w = resized.shape[-2:]
assert (h, w) == (
size, int(W / H * size)
), f"mismatched after resize: (h, w) == {(h, w)} but {(size, int(W / H * size))} expected"
resized = cv.resize(img, 256, constraint='shorter')
h, w = resized.shape[-2:]
assert (h, w) == (
size, int(W / H * size)
), f"mismatched after resize: (h, w) == {(h, w)} but {(size, int(W / H * size))} expected"
resized = cv.resize(img, 256, constraint='longer')
h, w = resized.shape[-2:]
assert (h, w) == (
int(H / W * size), size
), f"mismatched after resize: (h, w) == {(h, w)} but {(H / W * size, size)} expected"
def test_resize_pil():
from ml import cv
from PIL import Image
H, W, size = 720, 1280, 256
img = th.randn(3, H, W)
img = cv.fromTorch(img)
img = Image.fromarray(img)
assert img.size == (W, H)
assert img.mode == 'RGB'
resized = cv.resize(img, size)
w, h = resized.size
assert (h, w) == (
size, int(W / H * size)
), f"mismatched after resize: (h, w) == {(h, w)} but {(size, int(W / H * size))} expected"
resized = cv.resize(img, 256, constraint='shorter')
w, h = resized.size
assert (h, w) == (
size, int(W / H * size)
), f"mismatched after resize: (h, w) == {(h, w)} but {(size, int(W / H * size))} expected"
resized = cv.resize(img, 256, constraint='longer')
w, h = resized.size
assert (h, w) == (
int(H / W * size), size
), f"mismatched after resize: (h, w) == {(h, w)} but {(H / W * size, size)} expected"
def test_rfcn(tile_img):
from ml import cv
path = Path(tile_img)
img = cv.imread(path)
img2 = cv.resize(img, scale=0.5)
img = cv.imread(path)
model_dir = None # "/tmp/ml/checkpoints"
detector = rfcn(pooling=2, model_dir=model_dir, force_reload=True)
assert detector.with_rpn
rois, dets, pooled = detector.detect(img, return_rpn=True)
print('dets:', [tuple(det.shape) for det in dets], dets)
print('rois:', [tuple(roi.shape) for roi in rois])
print('pooled:', [tuple(feats.shape) for feats in pooled])
cv.render(img,
dets[0],
score_thr=0.01,
classes=COCO80_CLASSES,
path=f"export/{path.name[:-4]}-rfcn.jpg")
def __call__(self, img):
return cv.resize(img, self.scale, self.width, self.height,
self.interpolation)