Move tests outside package (#104)

tests/data/dataloader/yolosegment.py

@@ -0,0 +1,87 @@
+import cv2
+import hydra
+
+from ultralytics.yolo.data import build_dataloader
+from ultralytics.yolo.utils import ROOT
+from ultralytics.yolo.utils.plotting import plot_images
+
+DEFAULT_CONFIG = ROOT / "yolo/utils/configs/default.yaml"
+
+
+class Colors:
+    # Ultralytics color palette https://ultralytics.com/
+    def __init__(self):
+        # hex = matplotlib.colors.TABLEAU_COLORS.values()
+        hexs = ('FF3838', 'FF9D97', 'FF701F', 'FFB21D', 'CFD231', '48F90A', '92CC17', '3DDB86', '1A9334', '00D4BB',
+                '2C99A8', '00C2FF', '344593', '6473FF', '0018EC', '8438FF', '520085', 'CB38FF', 'FF95C8', 'FF37C7')
+        self.palette = [self.hex2rgb(f'#{c}') for c in hexs]
+        self.n = len(self.palette)
+
+    def __call__(self, i, bgr=False):
+        c = self.palette[int(i) % self.n]
+        return (c[2], c[1], c[0]) if bgr else c
+
+    @staticmethod
+    def hex2rgb(h):  # rgb order (PIL)
+        return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))
+
+
+colors = Colors()  # create instance for 'from utils.plots import colors'
+
+
+def plot_one_box(x, img, color=None, label=None, line_thickness=None):
+    import random
+
+    # Plots one bounding box on image img
+    tl = line_thickness or round(0.002 * (img.shape[0] + img.shape[1]) / 2) + 1  # line/font thickness
+    color = color or [random.randint(0, 255) for _ in range(3)]
+    c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))
+    cv2.rectangle(img, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA)
+    if label:
+        tf = max(tl - 1, 1)  # font thickness
+        t_size = cv2.getTextSize(label, 0, fontScale=tl / 3, thickness=tf)[0]
+        c2 = c1[0] + t_size[0], c1[1] - t_size[1] - 3
+        cv2.rectangle(img, c1, c2, color, -1, cv2.LINE_AA)  # filled
+        cv2.putText(
+            img,
+            label,
+            (c1[0], c1[1] - 2),
+            0,
+            tl / 3,
+            [225, 255, 255],
+            thickness=tf,
+            lineType=cv2.LINE_AA,
+        )
+
+
+@hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
+def test(cfg):
+    cfg.task = "segment"
+    cfg.mode = "train"
+    dataloader, _ = build_dataloader(
+        cfg=cfg,
+        batch_size=4,
+        img_path="/d/dataset/COCO/coco128-seg/images",
+        stride=32,
+        label_path=None,
+        mode=cfg.mode,
+    )
+
+    for d in dataloader:
+        images = d["img"]
+        masks = d["masks"]
+        cls = d["cls"].squeeze(-1)
+        bboxes = d["bboxes"]
+        paths = d["im_file"]
+        batch_idx = d["batch_idx"]
+        result = plot_images(images, batch_idx, cls, bboxes, masks, paths=paths)
+        cv2.imshow("p", result)
+        if cv2.waitKey(0) == ord("q"):
+            break
+
+
+if __name__ == "__main__":
+    test()
+    # test(augment=True, rect=False)
+    # test(augment=False, rect=True)
+    # test(augment=False, rect=False)