我试图创建一个旋转的图像是白色的，但这不起作用。图像总是变成黑色。
我怎么能做到这一点？

def rotate_image(image):
    # Convert the image to a NumPy array
    image_array = np.array(image)

    # Set the fill color (RGB format)
    fill_color = (255, 255, 255)  # White color

    # Define the rotation angle
    rotation_angle = random.randint(1, 360)

    # Perform rotation using OpenCV
    rows, cols = image_array.shape[:2]
    M = cv2.getRotationMatrix2D((cols / 2, rows / 2), rotation_angle, 1)
    rotated_array = cv2.warpAffine(image_array, M, (cols, rows), borderValue=fill_color)
    
    # Convert the rotated array back to an image
    rotated_image = Image.fromarray(rotated_array)

    # Save the rotated image as a PNG file
    rotated_image.save("test1.png")
    
    return rotated_image

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的数据
下面是我使用它的代码：

def get_dataset_batch(batch_size=2):
    flip = False
    base_image = Image.open("star_map_base.png")
    train_A = []
    train_B = []
    
    for i in range(0, batch_size):
        if flip:
            turbulence_size = random.choice([1, 2, 3, 4])
            turbulence_image = Image.open("turbulence.jpg")
            x = random.randint(0, 4096 - IMG_SIZE * turbulence_size)
            y = random.randint(0, 2136 - IMG_SIZE * turbulence_size)
            crop_actual_rect = (x, y, x + IMG_SIZE * turbulence_size, y + IMG_SIZE * turbulence_size)
            cropped_actual = turbulence_image.crop(crop_actual_rect)
            cropped_actual = cropped_actual.resize((IMG_SIZE, IMG_SIZE))
        else:
            helix_size = random.choice([1, 2, 3, 4, 5, 6, 7])
            helix_image = Image.open("helix_bw_base.jpg")
            x = random.randint(0, 4096 - IMG_SIZE * helix_size)
            y = random.randint(0, 4096 - IMG_SIZE * helix_size)
            crop_actual_rect = (x, y, x + IMG_SIZE * helix_size, y + IMG_SIZE * helix_size)
            cropped_actual = helix_image.crop(crop_actual_rect)
            cropped_actual = cropped_actual.resize((IMG_SIZE, IMG_SIZE))
        
        flip = not flip

        cropped_actual = cropped_actual.convert('LA')

        star_overlayed = cropped_actual
        star_overlayed = rotate_image(star_overlayed)
        star_overlayed = star_overlayed.convert('L')
        star_overlayed = Image.fromarray(transform(image=np.asarray(star_overlayed))["image"] / 1)
        star_overlayed = star_overlayed.convert('LA')

        ca = star_overlayed.copy()
        ca = ca.convert('L')
        
        base_image = base_image.convert('RGBA')
        star_overlayed = star_overlayed.convert('RGBA')
        overlaid_image = overlay_images(star_overlayed, base_image)
        overlaid_image = Image.fromarray(overlaid_image)
        
        star_overlayed = overlaid_image.convert('L')
        a = np.asarray(ca, dtype="float32").reshape(1, IMG_SIZE, IMG_SIZE, 1) / 512
        b = np.asarray(star_overlayed, dtype="float32").reshape(1, IMG_SIZE, IMG_SIZE, 1) / 512
        train_A.append(a)
        train_B.append(b)
    
    return train_A, train_B

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