def load_mosaic9()

in utils/datasets.py [0:0]

• 53 lines of code
• 17 McCabe index (conditional complexity)

def load_mosaic9(self, index):
    # loads images in a 9-mosaic

    labels9, segments9 = [], []
    s = self.img_size
    indices = [index] + random.choices(self.indices, k=8)  # 8 additional image indices
    for i, index in enumerate(indices):
        # Load image
        img, _, (h, w) = load_image(self, index)

        # place img in img9
        if i == 0:  # center
            img9 = np.full((s * 3, s * 3, img.shape[2]), 114, dtype=np.uint8)  # base image with 4 tiles
            h0, w0 = h, w
            c = s, s, s + w, s + h  # xmin, ymin, xmax, ymax (base) coordinates
        elif i == 1:  # top
            c = s, s - h, s + w, s
        elif i == 2:  # top right
            c = s + wp, s - h, s + wp + w, s
        elif i == 3:  # right
            c = s + w0, s, s + w0 + w, s + h
        elif i == 4:  # bottom right
            c = s + w0, s + hp, s + w0 + w, s + hp + h
        elif i == 5:  # bottom
            c = s + w0 - w, s + h0, s + w0, s + h0 + h
        elif i == 6:  # bottom left
            c = s + w0 - wp - w, s + h0, s + w0 - wp, s + h0 + h
        elif i == 7:  # left
            c = s - w, s + h0 - h, s, s + h0
        elif i == 8:  # top left
            c = s - w, s + h0 - hp - h, s, s + h0 - hp

        padx, pady = c[:2]
        x1, y1, x2, y2 = [max(x, 0) for x in c]  # allocate coords

        # Labels
        labels, segments = self.labels[index].copy(), self.segments[index].copy()
        if labels.size:
            labels[:, 1:] = xywhn2xyxy(labels[:, 1:], w, h, padx, pady)  # normalized xywh to pixel xyxy format
            segments = [xyn2xy(x, w, h, padx, pady) for x in segments]
        labels9.append(labels)
        segments9.extend(segments)

        # Image
        img9[y1:y2, x1:x2] = img[y1 - pady:, x1 - padx:]  # img9[ymin:ymax, xmin:xmax]
        hp, wp = h, w  # height, width previous

    # Offset
    yc, xc = [int(random.uniform(0, s)) for _ in self.mosaic_border]  # mosaic center x, y
    img9 = img9[yc:yc + 2 * s, xc:xc + 2 * s]

    # Concat/clip labels
    labels9 = np.concatenate(labels9, 0)
    labels9[:, [1, 3]] -= xc
    labels9[:, [2, 4]] -= yc
    c = np.array([xc, yc])  # centers
    segments9 = [x - c for x in segments9]

    for x in (labels9[:, 1:], *segments9):
        np.clip(x, 0, 2 * s, out=x)  # clip when using random_perspective()
    # img9, labels9 = replicate(img9, labels9)  # replicate

    # Augment
    img9, labels9 = random_perspective(img9, labels9, segments9,
                                       degrees=self.hyp['degrees'],
                                       translate=self.hyp['translate'],
                                       scale=self.hyp['scale'],
                                       shear=self.hyp['shear'],
                                       perspective=self.hyp['perspective'],
                                       border=self.mosaic_border)  # border to remove

    return img9, labels9