__author__ = "Simon Nilsson"

import os
from subprocess import PIPE, Popen
from tkinter import *
from tkinter import filedialog
from typing import Dict, Optional

import cv2
import pandas as pd
from PIL import Image, ImageTk
from tabulate import tabulate

try:
    from typing import Literal
except ImportError:
    from typing_extensions import Literal

import simba
from simba.mixins.config_reader import ConfigReader
from simba.utils.checks import (check_file_exist_and_readable, check_float,
                                check_int)
from simba.utils.errors import FrameRangeError
from simba.utils.printing import stdout_success
from simba.utils.read_write import (get_all_clf_names, get_fn_ext,
                                    get_video_meta_data, read_config_entry,
                                    read_df, write_df)


class LabellingInterface(ConfigReader):
    """
    Launch ``standard`` or ``pseudo``-labelling (annotation) GUI interface in SimBA.

    :parameter str config_path: path to SimBA project config file in Configparser format
    :parameter str file_path: Path to video that is to be annotated
    :parameter str setting: String representing annotation method. OPTIONS: ``from_scratch`` or ``pseudo``
    :parameter dict threshold_dict: If setting ``pseudo``, threshold_dict dict contains the machine probability thresholds, with the classifier
        names as keys and the classification probabilities as values, e.g. {'Attack': 0.40, 'Sniffing': 0.7).
    :parameter bool continuing: If True, continouing previously started annotation session.

    .. note::
       Tutorial <https://github.com/sgoldenlab/simba/blob/master/docs/label_behavior.md>`__.

    Examples
    ----------
    >>> select_labelling_video(config_path='MyConfigPath', threshold_dict={'Attack': 0.4}, file_path='MyVideoFilePath', setting='pseudo', continuing=False)
    """

    def __init__(
        self,
        config_path: str,
        file_path: str,
        threshold_dict: Optional[Dict[str, float]] = None,
        setting: Literal["from_scratch", "pseudo"] = "pseudo",
        continuing: bool = False,
    ):
        ConfigReader.__init__(self, config_path=config_path)
        self.padding, self.file_path = 5, file_path
        self.frm_no, self.threshold_dict = 0, threshold_dict
        self.setting = setting
        self.play_video_script_path = os.path.join(
            os.path.dirname(simba.__file__), "play_annotation_video.py"
        )
        _, self.video_name, _ = get_fn_ext(filepath=file_path)
        self.features_extracted_file_path = os.path.join(
            self.features_dir, self.video_name + "." + self.file_type
        )
        self.targets_inserted_file_path = os.path.join(
            self.targets_folder, self.video_name + "." + self.file_type
        )
        self.machine_results_file_path = os.path.join(
            self.machine_results_dir, self.video_name + "." + self.file_type
        )
        self.video_path = file_path
        self.cap = cv2.VideoCapture(self.video_path)
        self.video_meta_data = get_video_meta_data(video_path=self.video_path)
        self.frame_lst = list(range(0, self.video_meta_data["frame_count"]))
        self.max_frm_no = max(self.frame_lst)
        self.target_lst = get_all_clf_names(config=self.config, target_cnt=self.clf_cnt)
        self.max_frm_size = 1080, 650
        self.main_window = Toplevel()
        if continuing:
            check_file_exist_and_readable(file_path=self.targets_inserted_file_path)
            check_file_exist_and_readable(file_path=self.features_extracted_file_path)
            self.data_df = read_df(self.targets_inserted_file_path, self.file_type)
            self.data_df_features = read_df(
                self.features_extracted_file_path, self.file_type
            )
            missing_idx = self.data_df_features.index.difference(self.data_df.index)
            if len(missing_idx) > 0:
                self.data_df_features = self.data_df_features.iloc[
                    self.data_df_features.index.difference(self.data_df.index)
                ]
                self.data_df = pd.concat(
                    [self.data_df, self.data_df_features], axis=0
                ).sort_index()
            self.main_window.title(
                "SIMBA ANNOTATION INTERFACE (CONTINUING ANNOTATIONS) - {}".format(
                    self.video_name
                )
            )
            try:
                self.frm_no = read_config_entry(
                    self.config, "Last saved frames", self.video_name, data_type="int"
                )
            except ValueError:
                pass
        else:
            if setting == "from_scratch":
                check_file_exist_and_readable(
                    file_path=self.features_extracted_file_path
                )
                self.data_df = read_df(
                    self.features_extracted_file_path, self.file_type
                )
                self.main_window.title(
                    "SIMBA ANNOTATION INTERFACE (ANNOTATING FROM SCRATCH) - {}".format(
                        self.video_name
                    )
                )
                for target in self.target_lst:
                    self.data_df[target] = 0
            elif setting == "pseudo":
                check_file_exist_and_readable(file_path=self.machine_results_file_path)
                self.data_df = read_df(self.machine_results_file_path, self.file_type)
                for target in self.target_lst:
                    self.data_df.loc[
                        self.data_df["Probability_{}".format(target)]
                        > self.threshold_dict[target],
                        target,
                    ] = 1
                    self.data_df.loc[
                        self.data_df["Probability_{}".format(target)]
                        <= self.threshold_dict[target],
                        target,
                    ] = 0
                self.main_window.title(
                    "SIMBA ANNOTATION INTERFACE (PSEUDO-LABELLING) - {}".format(
                        self.video_name
                    )
                )
        self.data_df_targets = self.data_df[self.target_lst]
        self.folder = Frame(self.main_window)
        self.buttons_frm = Frame(self.main_window, bd=2, width=700, height=300)
        self.current_frm_n = IntVar(self.main_window, value=self.frm_no)
        self.change_frm_box = Entry(
            self.buttons_frm, width=7, textvariable=self.current_frm_n
        )
        self.frame_number_lbl = Label(self.buttons_frm, text="Frame number")
        self.forward_btn = Button(
            self.buttons_frm,
            text=">",
            command=lambda: self.__advance_frame(
                new_frm_number=int(self.current_frm_n.get() + 1)
            ),
        )
        self.backward_btn = Button(
            self.buttons_frm,
            text="<",
            command=lambda: self.__advance_frame(
                new_frm_number=int(self.current_frm_n.get() - 1)
            ),
        )
        self.forward_max_btn = Button(
            self.buttons_frm,
            text=">>",
            command=lambda: self.__advance_frame(len(self.frame_lst) - 1),
        )
        self.backward_max_btn = Button(
            self.buttons_frm, text="<<", command=lambda: self.__advance_frame(0)
        )
        self.select_frm_btn = Button(
            self.buttons_frm,
            text="Jump to selected frame",
            command=lambda: self.__advance_frame(
                new_frm_number=int(self.change_frm_box.get())
            ),
        )
        self.jump_frame = Frame(self.main_window)
        self.jump = Label(self.jump_frame, text="Jump Size:")
        self.jump_size = Scale(
            self.jump_frame, from_=0, to=100, orient=HORIZONTAL, length=200
        )
        self.jump_size.set(0)
        self.jump_back = Button(
            self.jump_frame,
            text="<<",
            command=lambda: self.__advance_frame(
                int(self.change_frm_box.get()) - self.jump_size.get()
            ),
        )
        self.jump_forward = Button(
            self.jump_frame,
            text=">>",
            command=lambda: self.__advance_frame(
                int(self.change_frm_box.get()) + self.jump_size.get()
            ),
        )

        self.folder.grid(row=0, column=1, sticky=N)
        self.buttons_frm.grid(row=1, column=0)
        self.change_frm_box.grid(row=0, column=1)
        self.forward_btn.grid(row=1, column=3, sticky=E, padx=self.padding)
        self.backward_btn.grid(row=1, column=1, sticky=W, padx=self.padding)
        self.change_frm_box.grid(row=1, column=1)
        self.forward_max_btn.grid(row=1, column=4, sticky=W, padx=self.padding)
        self.backward_max_btn.grid(row=1, column=0, sticky=W, padx=self.padding)
        self.select_frm_btn.grid(row=2, column=1, sticky=N)
        self.jump_frame.grid(row=2, column=0)
        self.jump.grid(row=0, column=0, sticky=W)
        self.jump_size.grid(row=0, column=1, sticky=W)
        self.jump_back.grid(row=0, column=2, sticky=E)
        self.jump_forward.grid(row=0, column=3, sticky=W)

        ## Behavior Checkbox
        self.check_frame = Frame(self.main_window, bd=2, width=300, height=500)
        self.check_frame.grid(row=0, column=1)
        self.check_behavior_lbl = Label(self.check_frame, text="Check Behavior:")
        self.check_behavior_lbl.config(font=("Calibri", 16))
        self.check_behavior_lbl.grid(sticky=N)

        self.checkboxes = {}
        for target_cnt, target in enumerate(self.target_lst):
            self.checkboxes[target] = {}
            self.checkboxes[target]["name"] = target
            self.checkboxes[target]["var"] = IntVar()
            self.checkboxes[target]["cb"] = Checkbutton(
                self.check_frame,
                text=target,
                variable=self.checkboxes[target]["var"],
                command=lambda k=self.checkboxes[target][
                    "name"
                ]: self.save_behavior_in_frm(
                    frame_number=int(self.current_frm_n.get()), target=k
                ),
            )
            self.checkboxes[target]["cb"].grid(row=target_cnt + 1, sticky=W)
            self.checkboxes[target]["var"].set(
                self.data_df_targets[target].iloc[self.current_frm_n.get()]
            )

        self.range_on = IntVar(value=0)
        self.range_frames = Frame(self.main_window)
        self.range_frames.grid(row=1, column=1, sticky=S)
        self.select_range = Checkbutton(
            self.range_frames, text="Frame range", variable=self.range_on
        )
        self.select_range.grid(row=0, column=0, sticky=W)
        self.first_frame = Entry(self.range_frames, width=7)
        self.first_frame.grid(row=0, column=1, sticky=E)
        self.to_label = Label(self.range_frames, text=" to ")
        self.to_label.grid(row=0, column=2, sticky=E)
        self.last_frame = Entry(self.range_frames, width=7)
        self.last_frame.grid(row=0, column=3, sticky=E)

        save = Button(
            self.main_window,
            text="Save Range",
            command=lambda: self.__save_behavior_in_range(
                self.first_frame.get(), self.last_frame.get()
            ),
        )
        save.grid(row=2, column=1, sticky=N)

        self.generate = Button(
            self.main_window,
            text="Save Annotations",
            command=lambda: self.__save_results(),
            fg="blue",
        )
        self.generate.config(font=("Calibri", 16))
        self.generate.grid(row=10, column=1, sticky=N)

        self.video_player_frm = Frame(self.main_window, width=100, height=100)
        self.video_player_frm.grid(row=0, column=2, sticky=N)
        self.play_video_btn = Button(
            self.video_player_frm, text="Open Video", command=self.__play_video
        )
        self.play_video_btn.grid(sticky=N, pady=10)
        self.video_key_lbls = Label(
            self.video_player_frm,
            text="\n\n  Keyboard shortcuts for video navigation: \n p = Pause/Play"
            "\n\n After pressing pause:"
            "\n o = +2 frames \n e = +10 frames \n w = +1 second"
            "\n\n t = -2 frames \n s = -10 frames \n x = -1 second"
            "\n\n q = Close video window \n\n",
        )
        self.video_key_lbls.grid(sticky=W)
        self.update_img_from_video = Button(
            self.video_player_frm,
            text="Show current video frame",
            command=self.__update_frame_from_video,
        )
        self.update_img_from_video.grid(sticky=N)
        self.__bind_shortcut_keys()
        self.key_presses_lbl = Label(
            self.video_player_frm,
            text="\n\n Keyboard shortcuts for frame navigation: \n Right Arrow = +1 frame"
            "\n Left Arrow = -1 frame"
            "\n Ctrl + s = Save annotations file"
            "\n Ctrl + a = +1 frame and keep choices"
            "\n Ctrl + p = Show annotation statistics"
            "\n Ctrl + l = Last frame"
            "\n Ctrl + o = First frame",
        )
        self.key_presses_lbl.grid(sticky=S)
        self.__read_frm(frm_number=0)
        self.main_window.mainloop()

    def __bind_shortcut_keys(self):
        self.main_window.bind("<Control-s>", lambda x: self.__save_results())
        self.main_window.bind(
            "<Control-a>",
            lambda x: self.__advance_frame(
                new_frm_number=int(self.current_frm_n.get() + 1),
                save_and_keep_checks=True,
            ),
        )
        self.main_window.bind(
            "<Control-p>", lambda x: self.print_annotation_statistics()
        )
        self.main_window.bind(
            "<Right>",
            lambda x: self.__advance_frame(
                new_frm_number=int(self.current_frm_n.get() + 1)
            ),
        )
        self.main_window.bind(
            "<Left>",
            lambda x: self.__advance_frame(
                new_frm_number=int(self.current_frm_n.get() - 1)
            ),
        )
        self.main_window.bind(
            "<Control-l>",
            lambda x: self.__advance_frame(new_frm_number=self.max_frm_no),
        )
        self.main_window.bind("<Control-o>", lambda x: self.__advance_frame(0))

    def print_annotation_statistics(self):
        table_view = [
            ["Video name", self.video_name],
            ["Video frames", self.video_meta_data["frame_count"]],
        ]
        for target in self.target_lst:
            present = len(self.data_df_targets[self.data_df_targets[target] == 1])
            absent = len(self.data_df_targets[self.data_df_targets[target] == 0])
            table_view.append([target + " present labels", present])
            table_view.append([target + " absent labels", absent])
            table_view.append(
                [target + " % present", present / self.video_meta_data["frame_count"]]
            )
            table_view.append(
                [target + " % absent", absent / self.video_meta_data["frame_count"]]
            )
        headers = ["VARIABLE", "VALUE"]
        print(tabulate(table_view, headers, tablefmt="github"))

    def __play_video(self):
        p = Popen(
            "python {}".format(self.play_video_script_path),
            stdin=PIPE,
            stdout=PIPE,
            shell=True,
        )
        main_project_dir = os.path.dirname(self.config_path)
        p.stdin.write(bytes(self.video_path, "utf-8"))
        p.stdin.close()
        temp_file = os.path.join(main_project_dir, "subprocess.txt")
        with open(temp_file, "w") as text_file:
            text_file.write(str(p.pid))

    def __update_frame_from_video(self):
        f = open(
            os.path.join(os.path.dirname(self.config_path), "labelling_info.txt"), "r+"
        )
        os.fsync(f.fileno())
        vid_frame_no = int(f.readline())
        self.__advance_frame(new_frm_number=vid_frame_no)
        f.close()

    def __read_frm(self, frm_number=None):
        self.cap.set(1, frm_number)
        _, self.current_frm_npy = self.cap.read()
        self.current_frm_npy = cv2.cvtColor(self.current_frm_npy, cv2.COLOR_RGB2BGR)
        self.current_frm_pil = Image.fromarray(self.current_frm_npy)
        self.current_frm_pil.thumbnail(self.max_frm_size, Image.ANTIALIAS)
        self.current_frm_pil = ImageTk.PhotoImage(
            master=self.main_window, image=self.current_frm_pil
        )
        self.video_frame = Label(self.main_window, image=self.current_frm_pil)
        self.video_frame.image = self.current_frm_pil
        self.video_frame.grid(row=0, column=0)

    def __advance_frame(self, new_frm_number: int = None, save_and_keep_checks=False):
        if new_frm_number > self.max_frm_no:
            print(
                "FRAME {} CANNOT BE SHOWN - YOU ARE VIEWING THE FINAL FRAME OF THE VIDEO (FRAME NUMBER {})".format(
                    str(new_frm_number), str(self.max_frm_no)
                )
            )
            self.current_frm_n = IntVar(value=self.max_frm_no)
            self.change_frm_box.delete(0, END)
            self.change_frm_box.insert(0, self.current_frm_n.get())
        elif new_frm_number < 0:
            print(
                "FRAME {} CANNOT BE SHOWN - YOU ARE VIEWING THE FIRST FRAME OF THE VIDEO (FRAME NUMBER {})".format(
                    str(new_frm_number), str(self.max_frm_no)
                )
            )
            self.current_frm_n = IntVar(value=0)
            self.change_frm_box.delete(0, END)
            self.change_frm_box.insert(0, self.current_frm_n.get())
        else:
            self.__create_print_statements()
            self.current_frm_n = IntVar(value=new_frm_number)
            self.change_frm_box.delete(0, END)
            self.change_frm_box.insert(0, self.current_frm_n.get())
            if not save_and_keep_checks:
                for target in self.target_lst:
                    self.checkboxes[target]["var"].set(
                        self.data_df_targets[target].loc[int(self.current_frm_n.get())]
                    )
            else:
                for target in self.target_lst:
                    self.checkboxes[target]["var"].set(
                        self.data_df_targets[target].loc[
                            int(self.current_frm_n.get() - 1)
                        ]
                    )
                    self.save_behavior_in_frm(target=target)
            self.__read_frm(frm_number=int(self.current_frm_n.get()))

    def __save_behavior_in_range(self, start_frm=None, end_frm=None):
        if not self.range_on.get():
            raise FrameRangeError(
                "SAVE RANGE ERROR: TO SAVE RANGE OF FRAMES, TICK THE `Frame range` checkbox before clicking `Save Range`"
            )
        else:
            check_int(
                "START FRAME", int(start_frm), max_value=self.max_frm_no, min_value=0
            )
            check_int("END FRAME", int(end_frm), max_value=self.max_frm_no, min_value=0)
            for frm_no in range(int(start_frm), int(end_frm) + 1):
                for target in self.target_lst:
                    self.data_df_targets[target].loc[frm_no] = self.checkboxes[target][
                        "var"
                    ].get()
            self.__read_frm(frm_number=int(end_frm))
            self.change_frm_box.delete(0, END)
            self.change_frm_box.insert(0, end_frm)
        self.__create_print_statements(
            frame_range=True, start_frame=start_frm, end_frame=end_frm
        )

    def save_behavior_in_frm(self, frame_number=None, target=None):
        self.data_df_targets[target].loc[
            int(self.current_frm_n.get())
        ] = self.checkboxes[target]["var"].get()

    def __save_results(self):
        self.save_df = read_df(self.features_extracted_file_path, self.file_type)
        self.save_df = pd.concat([self.save_df, self.data_df_targets], axis=1)
        try:
            write_df(self.save_df, self.file_type, self.targets_inserted_file_path)
        except Exception as e:
            print(e, "SIMBA ERROR: File for video {} could not be saved.")
            raise FileExistsError
        stdout_success(
            msg=f"SAVED: Annotation file for video {self.video_name} saved within the project_folder/csv/targets_inserted directory."
        )
        if not self.config.has_section("Last saved frames"):
            self.config.add_section("Last saved frames")
        self.config.set(
            "Last saved frames", str(self.video_name), str(self.current_frm_n.get())
        )
        with open(self.config_path, "w") as configfile:
            self.config.write(configfile)

    def __create_print_statements(
        self, frame_range: bool = None, start_frame: int = None, end_frame: int = None
    ):
        print("USER FRAME SELECTION(S):")
        if not frame_range:
            for target in self.target_lst:
                target_present_choice = self.checkboxes[target]["var"].get()
                if target_present_choice == 0:
                    print(
                        "{} ABSENT IN FRAME {}".format(target, self.current_frm_n.get())
                    )
                if target_present_choice == 1:
                    print(
                        "{} PRESENT IN FRAME {}".format(
                            target, self.current_frm_n.get()
                        )
                    )

        if frame_range:
            for target in self.target_lst:
                target_present_choice = self.checkboxes[target]["var"].get()
                if target_present_choice == 1:
                    print(
                        "{} PRESENT IN FRAMES {} to {}".format(
                            target, str(start_frame), str(end_frame)
                        )
                    )
                elif target_present_choice == 0:
                    print(
                        "{} ABSENT IN FRAMES {} to {}".format(
                            target, str(start_frame), str(end_frame)
                        )
                    )


def select_labelling_video(
    config_path: str = None,
    threshold_dict=None,
    setting: str = None,
    continuing: bool = None,
    video_file_path=None,
):
    if setting is not "pseudo":
        video_file_path = filedialog.askopenfilename()
    else:
        threshold_dict_values = {}
        for k, v in threshold_dict.items():
            check_float(name=k, value=float(v.entry_get), min_value=0.0, max_value=1.0)
            threshold_dict_values[k] = float(v.entry_get)
        threshold_dict = threshold_dict_values

    check_file_exist_and_readable(video_file_path)
    video_meta = get_video_meta_data(video_file_path)
    _, video_name, _ = get_fn_ext(video_file_path)
    print(threshold_dict)

    print("ANNOTATING VIDEO {}: ".format(video_name))
    print("VIDEO INFO")
    print(video_meta)
    _ = LabellingInterface(
        config_path=config_path,
        file_path=video_file_path,
        threshold_dict=threshold_dict,
        setting=setting,
        continuing=continuing,
    )


# test = select_labelling_video(config_path='/Users/simon/Desktop/troubleshooting/train_model_project/project_folder/project_config.ini',
#                           threshold_dict={'Attack': 0.4},
#                           setting='from_scratch',
#                           continuing=False)
