# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import json
import math
import platform
from pathlib import Path

from collections import defaultdict
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import font_manager
from matplotlib.backends.backend_agg import FigureCanvasAgg

from .....utils.file_interface import custom_open
from .....utils.fonts import PINGFANG_FONT_FILE_PATH


def deep_analyse(dataset_path, output, dataset_type="ShiTuRec"):
    """class analysis for dataset"""
    tags = ["train", "gallery", "query"]
    tags_info = dict()
    for tag in tags:
        anno_path = os.path.join(dataset_path, f"{tag}.txt")
        with custom_open(anno_path, "r") as f:
            lines = f.readlines()
            lines = [line.strip("\n").split(" ") for line in lines]
            num_images = len(lines)
            num_labels = len(set([int(line[1]) for line in lines]))
        tags_info[tag] = {
            "num_images": num_images,
            "num_labels": num_labels,
        }

    categories = list(tags_info.keys())
    num_images = [tags_info[category]['num_images'] for category in categories]
    num_labels = [tags_info[category]['num_labels'] for category in categories]

    # bar
    os_system = platform.system().lower()
    if os_system == "windows":
        plt.rcParams["font.sans-serif"] = "FangSong"
    else:
        font = font_manager.FontProperties(fname=PINGFANG_FONT_FILE_PATH, size=10)

    x = np.arange(len(categories))  # 标签位置
    width = 0.35  # 每个条形的宽度

    fig, ax = plt.subplots()
    rects1 = ax.bar(x - width/2, num_images, width, label="Num Images")
    rects2 = ax.bar(x + width/2, num_labels, width, label="Num Classes")

    # 添加一些文本标签
    ax.set_xlabel("集合", fontproperties=None if os_system == "windows" else font)
    ax.set_ylabel("数量", fontproperties=None if os_system == "windows" else font)
    ax.set_title("不同集合的图片和类别数量", fontproperties=None if os_system == "windows" else font)
    ax.set_xticks(x, fontproperties=None if os_system == "windows" else font)
    ax.set_xticklabels(categories)
    ax.legend()

    # 在条形图上添加数值标签
    def autolabel(rects):
        """Attach a text label above each bar in *rects*, displaying its height."""
        for rect in rects:
            height = rect.get_height()
            ax.annotate('{}'.format(height),
                        xy=(rect.get_x() + rect.get_width() / 2, height),
                        xytext=(0, 3),  # 3 points vertical offset
                        textcoords="offset points",
                        ha="center", va="bottom")

    autolabel(rects1)
    autolabel(rects2)

    fig.tight_layout()
    file_path = os.path.join(output, "histogram.png")
    fig.savefig(file_path, dpi=300)

    return {"histogram": os.path.join("check_dataset", "histogram.png")}