Simul-Back/visualize_app.py at main · SmGirls/Simul-Back · GitHub

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from flask import Flask, render_template, url_for, request, jsonify
from flask_restx import Resource, Namespace, Api
from flask_cors import CORS
import pandas as pd
import os
import json

app_visualize = Flask(__name__)

CORS(app_visualize)

colorList = ["crimson", "limegreen", "g", "r", "c", "m", "y", "k"]

# 시각화에 필요한 함수 - cuboid_data2,plotCubeAt2
def cuboid_data2(o, size=(1, 1, 1)):
    X = [[[0, 1, 0], [0, 0, 0], [1, 0, 0], [1, 1, 0]],
        [[0, 0, 0], [0, 0, 1], [1, 0, 1], [1, 0, 0]],
        [[1, 0, 1], [1, 0, 0], [1, 1, 0], [1, 1, 1]],
        [[0, 0, 1], [0, 0, 0], [0, 1, 0], [0, 1, 1]],
        [[0, 1, 0], [0, 1, 1], [1, 1, 1], [1, 1, 0]],
        [[0, 1, 1], [0, 0, 1], [1, 0, 1], [1, 1, 1]]]
    X = np.array(X).astype(float)
    for i in range(3):
        X[:, :, i] *= size[i]
    X += np.array(o)
    return X

def plotCubeAt2(positions, sizes=None, colors=None, **kwargs):
        if not isinstance(colors, (list, np.ndarray)): colors = ["C0"] * len(positions)
        if not isinstance(sizes, (list, np.ndarray)): sizes = [(1, 1, 1)] * len(positions)
        g = []
        for p, s, c in zip(positions, sizes, colors):
            g.append(cuboid_data2(p, size=s))
        return Poly3DCollection(np.concatenate(g),
                                facecolors=np.repeat(colors, 6), **kwargs)

# test
@app_visualize.route('/')
def webserver():
    return "hello"

# 실제 코드
@app_visualize.route('/simul',methods=['POST'])
def simulation():
    # 컨테이너 적재
    for t in range(len(containers)):
        packer = Packer()

        truckX = containers[t][0]
        truckY = containers[t][1]
        truckZ = containers[t][2]

        #무게 제약 -> 4번째 요소
        packer.add_bin(Bin('LB', truckX, truckY, truckZ, 10000.0))

        # 물류 등록 - (물류 이름, 가로, 세로, 높이, 무게) * 수량
        for i in range(len(items)):
            # 물류의 수량 만큼 곱해주기기
            each_items_cnt = int(items[i][5])
            # 물류의 수량이 0이면 안됨^^
            if each_items_cnt > 0:
                for _ in range(each_items_cnt):
                    packer.add_item(Item(items[i][0], items[i][1], items[i][2], items[i][3], items[i][4]))

        # packer.pack()
        packer.pack(bigger_first=False)  # 큰 것 우선

        positions = []
        sizes = []
        colors = []

        for b in packer.bins:
            print(":::::::::::", b.string())

            print("FITTED ITEMS:")
            # 적합한 물류는 list 만들어주기기
            fitted_list = []
            for item in b.items:
                print("====> ", item.string())
                x = float(item.position[0])
                y = float(item.position[1])
                z = float(item.position[2])
                positions.append((x, y, z))
                sizes.append(
                    (float(item.get_dimension()[0]), float(item.get_dimension()[1]), float(item.get_dimension()[2])))

                # 적합한 물류는 적재하고 item list에서 빼주기
                # print("적합 물류 정보 : ", item.name)
                fitted_list.append(item.name)
            print(fitted_list)
            fitted_rows = [i for i, item in enumerate(items) if item[0] in fitted_list]

            print("UNFITTED ITEMS:")
            for item in b.unfitted_items:
                print("====> ", item.string())

            print("***************************************************")
            print("***************************************************")

            # 적합한 물류들은 items에서 삭제해줌으로서 이미 컨테이너에 적재된 물류들은 물류 정보에서 제거
            for index in sorted(fitted_rows, reverse=True):
                del items[index]

        # 색깔 선정
        for i in range(len(b.items)):
            f = random.randint(0, 7)
            colors.append(colorList[f])

        # print(colors)

        fig = plt.figure()
        ax = fig.add_subplot(projection='3d')
        ax.set_aspect('auto')

        pc = plotCubeAt2(positions, sizes, colors=colors, edgecolor="k")
        ax.add_collection3d(pc)

        ax.set_xlim([0, truckX])
        ax.set_ylim([0, truckY])
        ax.set_zlim([0, truckZ])

        time.sleep(10)
        #plt.savefig("./share/static/images/result"+ os.getenv('START_ROW', '1') + ".png")
        #plt.savefig("./result.png")
        plt.savefig(img_name+".png")
if __name__ == '__main__':
    app_visualize.run(host="0.0.0.0", port=7001,debug=True)