import cv2
import matplotlib.pyplot as plt
import os


def plot_histogram_and_draw_lines(image_path, column_indices, y_range, results, image_index):
    # 讀取圖像
    image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)

    # 檢查圖像是否成功讀取
    if image is None:
        print(f"Error: Unable to read the image '{image_path}'.")
        return

    # 創建彩色圖像以便畫線
    image_color = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)

    for column_index in column_indices:
        # 檢查 column_index 是否在圖像範圍內
        if column_index >= image.shape[1]:
            continue

        # 檢查 y_range 是否在圖像範圍內
        if max(y_range) >= image.shape[0]:
            continue

        # 選擇特定的列和 y 坐標範圍
        column_data = image[y_range, column_index]

        # 反轉 y 坐標範圍
        y_coordinates_reversed = list(y_range)[::-1]

        # 查找從灰度值 250 開始並遵循規則的最高點
        start_index = next((i for i, value in enumerate(column_data) if value <= 250), None)
        if start_index is None:
            continue

        start_y_coord = y_coordinates_reversed[start_index]

        decreasing = True
        highest_point = None
        potential_highest = None

        for i in range(start_index, len(column_data) - 40):
            current_value = column_data[i]
            next_values = column_data[i + 1:i + 5]

            if decreasing:
                if all(next_value > current_value for next_value in next_values):
                    decreasing = False
                    potential_highest = (y_coordinates_reversed[i + 3], column_data[i + 3])
            else:
                if all(next_value > potential_highest[1] for next_value in next_values):
                    potential_highest = (y_coordinates_reversed[i + 2], column_data[i + 2])
                elif all(next_value < current_value for next_value in next_values):
                    highest_point = potential_highest
                    break

        if highest_point:
            highest_y_coord, highest_grayscale_value = highest_point

            # 計算Y坐標的差值
            y_difference = start_y_coord - highest_y_coord

            # 計算Y坐標差值乘以2.4/1000的結果
            result = y_difference * 2.4 / 1000

            # 在圖像上畫線，從起點畫到最高點
            cv2.line(image_color, (column_index, image.shape[0] - start_y_coord),
                     (column_index, image.shape[0] - highest_y_coord), (0, 0, 255), 1)

            # 保存結果值和圖號到列表
            results.append((image_index, result))

    # 顯示並保存帶有畫線的圖像
    plt.imshow(cv2.cvtColor(image_color, cv2.COLOR_BGR2RGB))
    plt.title('Image with lines')
    plt.show()

    # 獲取輸出圖像的文件名和路徑
    base_filename = os.path.splitext(os.path.basename(image_path))[0]
    output_filename = f'{base_filename}.png'
    output_path = os.path.join(os.path.dirname(image_path), output_filename)
    cv2.imwrite(output_path, image_color)


def process_folder(folder_path, column_indices, y_range):
    all_results = []
    image_index = 0
    for filename in os.listdir(folder_path):
        if filename.endswith(('.bmp', '.png', '.jpg', '.jpeg')):
            image_path = os.path.join(folder_path, filename)
            plot_histogram_and_draw_lines(image_path, column_indices, y_range, all_results, image_index)
            image_index += 1

    # 打印所有結果值，每10個空一行
    for i, (image_index, result) in enumerate(all_results, start=1):
        print(f'Image {image_index + 1}: Result: {result:.4f}')
        if i % 10 == 0:
            print()  # 插入空行


if __name__ == '__main__':
    folder_path = r"D:\Code\Project\Medeologix\Python\Size\TIS_test\joe\1092"
    x_range = 5472
    num_segments = 10

    column_indices = [x * x_range // num_segments for x in range(num_segments)]
    y_range_partial = range(0, 3648)  # 嘗試不同的範圍

    process_folder(folder_path, column_indices, y_range_partial)