# -*- coding: utf-8 -*-
"""
Created on Thu Mar 27 16:09:07 2025

@author: ym
"""
import os
import sys
import cv2
import pickle
import numpy as np
from pathlib import Path
from scipy.spatial.distance import cdist

from .dotrack.dotracks_back import doBackTracks
from .dotrack.dotracks_front import doFrontTracks 
from .utils.drawtracks import plot_frameID_y2, draw_all_trajectories
from .utils.read_data import read_similar




class CameraEvent_:
    def __init__(self):
        self.cameraType = '',   # "front", "back"
        self.videoPath = '',
        self.imagePaths = [],
        self.yoloResnetTracker =[],
        self.tracking = None,

class ShoppingEvent_:
    def __init__(self):
        self.eventPath = ''
        self.eventName = ''
        self.barcode = ''
        self.eventType = '',   # "input", "output", "other"
        self.frontCamera = None
        self.backCamera = None
        self.one2n = []
    
    



def main():
    '''
    将一个对象读取，修改其中一个属性
    
    '''
    
    
    evt_pkfile = 'path.pickle'
    with open(evt_pkfile, 'rb') as f:
        ShoppingDict = pickle.load(f)
        
    savepath = ""
    
    back_camera = ShoppingDict["backCamera"]["cameraType"]        
    back_yrt = ShoppingDict["backCamera"]["yoloResnetTracker"]
    front_camera = ShoppingDict["frontCamera"]["cameraType"] 
    front_yrt = ShoppingDict["frontCamera"]["yoloResnetTracker"]
    yrts = [(back_camera, back_yrt), (front_camera, front_yrt)]
      
    
    shopping_event = ShoppingEvent_()    
    shopping_event.eventPath = ShoppingDict["eventPath"]
    shopping_event.eventName = ShoppingDict["eventName"]
    shopping_event.barcode = ShoppingDict["barcode"]
    
    yrtDict = {}
    event_tracks = []
    for camera_type, yrtOut in yrts:
        '''
        inputs: 
            yrtOut
            camera_type
        outputs:
            CameraEvent
        '''
        
        camera_event = CameraEvent_()
        

        
        '''================= 4. tracking ================='''
        '''(1) 生成用于 tracking 模块的 boxes、feats'''  
        bboxes = np.empty((0, 6), dtype=np.float64)
        trackerboxes = np.empty((0, 9), dtype=np.float64)
        trackefeats = {}
        for frameDict in yrtOut:            
            tboxes = frameDict["tboxes"]
            ffeats = frameDict["feats"]
            
            boxes = frameDict["bboxes"]
            bboxes = np.concatenate((bboxes, np.array(boxes)), axis=0)
            trackerboxes = np.concatenate((trackerboxes, np.array(tboxes)), axis=0)
            for i in range(len(tboxes)):
                fid, bid = int(tboxes[i, 7]), int(tboxes[i, 8])
                trackefeats.update({f"{fid}_{bid}": ffeats[f"{fid}_{bid}"]})
        

        '''(2) tracking, 后摄'''
        if CameraEvent["cameraType"] == "back":
            vts = doBackTracks(trackerboxes, trackefeats)
            vts.classify()
            event_tracks.append(("back", vts))
            
            
            
            camera_event.camera_type = camera_type
            camera_event.yoloResnetTracker = yrtOut
            camera_event.tracking = vts
            camera_event.videoPath = ShoppingDict["backCamera"]["videoPath"]  
            camera_event.imagePaths =  ShoppingDict["backCamera"]["imagePaths"] 
            shopping_event.backCamera = camera_event
            
            yrtDict["backyrt"] = yrtOut
        
        '''(2) tracking, 前摄'''    
        if  CameraEvent["cameraType"] == "front":
            vts = doFrontTracks(trackerboxes, trackefeats)
            vts.classify()
            event_tracks.append(("front", vts))
            
            camera_event.camera_type = camera_type
            camera_event.yoloResnetTracker = yrtOut
            camera_event.tracking = vts
            camera_event.videoPath = ShoppingDict["frontCamera"]["videoPath"]  
            camera_event.imagePaths =  ShoppingDict["frontCamera"]["imagePaths"] 
            shopping_event.backCamera = camera_event
            
            yrtDict["frontyrt"] = yrtOut
    
    
    name = Path(evt_pkfile).stem
    pf_path = os.path.join(savepath, name+"_new.pickle")
    with open(str(pf_path), 'wb') as f:
        pickle.dump(shopping_event, f)
        
        
        
    illus = [None, None]
    for CamerType, vts in event_tracks:
        if len(vts.tracks)==0: continue
        
        if CamerType == 'front':
            edgeline = cv2.imread("./tracking/shopcart/cart_tempt/board_ftmp_line.png")
            
            h, w = edgeline.shape[:2]
            # nh, nw = h//2, w//2
            # edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
            
            img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
            illus[0] = img_tracking

            plt = plot_frameID_y2(vts)
            plt.savefig(os.path.join(savepath_pipeline, "front_y2.png"))
            
        if CamerType == 'back':
            edgeline = cv2.imread("./tracking/shopcart/cart_tempt/edgeline.png")
            
            h, w = edgeline.shape[:2]
            # nh, nw = h//2, w//2
            # edgeline = cv2.resize(edgeline, (nw, nh), interpolation=cv2.INTER_AREA)
            
            img_tracking = draw_all_trajectories(vts, edgeline, savepath_pipeline, CamerType, draw5p=True)
            illus[1] = img_tracking
        










if __name__ == "__main__": 
    main()