模型輔助函數
讀取圖片、繪製邊界框、計算交並比、非極大值抑制等。這些函數會幫助模型處理輸入和輸出的數據，以及過濾掉不可靠的預測結果。
def load_images(img_names, model_size):
"""Loads images in a 4D array.

Args:
    img_names: A list of images names.
    model_size: The input size of the model.
    data_format: A format for the array returned
        ('channels_first' or 'channels_last').

Returns:
    A 4D NumPy array.
"""
imgs = []

for img_name in img_names:
    img = Image.open(img_name)
    img = img.resize(size=model_size)
    img = np.array(img, dtype=np.float32)
    img = np.expand_dims(img, axis=0)
    imgs.append(img)

imgs = np.concatenate(imgs)

return imgs

def load_class_names(file_name):
"""Returns a list of class names read from file_name."""
with open(file_name, 'r') as f:
class_names = f.read().splitlines()
return class_names

def draw_boxes(img_names, boxes_dicts, class_names, model_size):
"""Draws detected boxes.

Args:
    img_names: A list of input images names.
    boxes_dict: A class-to-boxes dictionary.
    class_names: A class names list.
    model_size: The input size of the model.

Returns:
    None.
"""
colors = ((np.array(color_palette("hls", 80)) * 255)).astype(np.uint8)
for num, img_name, boxes_dict in zip(range(len(img_names)), img_names,
                                     boxes_dicts):
    img = Image.open(img_name)
    draw = ImageDraw.Draw(img)
    font = ImageFont.truetype(font='../input/futur.ttf',
                              size=(img.size[0] + img.size[1]) // 100)
    resize_factor = \
        (img.size[0] / model_size[0], img.size[1] / model_size[1])
    for cls in range(len(class_names)):
        boxes = boxes_dict[cls]
        if np.size(boxes) != 0:
            color = colors[cls]
            for box in boxes:
                xy, confidence = box[:4], box[4]
                xy = [xy[i] * resize_factor[i % 2] for i in range(4)]
                x0, y0 = xy[0], xy[1]
                thickness = (img.size[0] + img.size[1]) // 200
                for t in np.linspace(0, 1, thickness):
                    xy[0], xy[1] = xy[0] + t, xy[1] + t
                    xy[2], xy[3] = xy[2] - t, xy[3] - t
                    draw.rectangle(xy, outline=tuple(color))
                text = '{} {:.1f}%'.format(class_names[cls],
                                           confidence * 100)
                text_size = draw.textsize(text, font=font)
                draw.rectangle(
                    [x0, y0 - text_size[1], x0 + text_size[0], y0],
                    fill=tuple(color))
                draw.text((x0, y0 - text_size[1]), text, fill='black',
                          font=font)

    display(img)