PoseCorrection/backend/video_to_photo.py

import os
import math

import cv2
from demo_func import run_openpose_for_normal
from PIL import Image
from analyse_jump import analyse_npy_side_jump, analyse_npy_side_pingban, analyse_npy_side_juanfu, \
    analyse_npy_side_gaotaitui, analyse_npy_side_shendun
import glob
import time
import os


def split_video(path):
    video_path = path
    os.path.split(path)
    tur = os.path.split(path)
    print("split_video1")
    print(path)
    print(tur[len(tur) - 1].split('.')[0])
    name = tur[len(tur) - 1].split('.')[0]
    if os.path.exists("./capture_image/" + name) == False:
        os.mkdir("./capture_image/" + name)
    cap = cv2.VideoCapture(video_path)
    FPS = cap.get(5)
    print(FPS)
    c = 1
    frameRate = 1
    if os.path.exists("./capture_image/" + name) == False:
        os.mkdir("./capture_image/" + name)

    while (True):
        ret, frame = cap.read()
        if ret:
            if (c % frameRate == 0):
                cv2.imwrite("./capture_image/" + name + "/capture_image" + str(c) + '.png', frame)
            c += 1
            cv2.waitKey(0)
        else:
            break
    cap.release()
    print(c)
    return c


def process_photo(name, c):
    print("process_photo" + name)
    for i in range(1, c):
        run_openpose_for_normal(i, name)
        # run_openpose_for_normal(i)


# 保存跑完模型后的视频
def gather_video(path):
    video_path = path

    os.path.split(path)
    tur = os.path.split(path)
    print(tur[len(tur) - 1].split('.')[0])
    name = tur[len(tur) - 1].split('.')[0]

    cap = cv2.VideoCapture(video_path)
    fps = cap.get(5)
    num_frames = len(os.listdir(r'./capture_image/' + name))
    print(num_frames)
    img_array = []
    im = Image.open("./capture_image/" + name + "/capture_image_result1.png")

    # img_width = 720
    # img_height = 1280
    k = 0
    for i in range(num_frames + 1):
        filename = "./capture_image/" + name + "/capture_image_result" + str(i) + ".png"
        k += 1
        img = cv2.imread(filename)

        if img is None:
            continue
        img_array.append(img)
    print(k)
    save_name = "./video/video_a/" + name + ".mp4"
    out = cv2.VideoWriter(save_name, cv2.VideoWriter_fourcc(*"mp4v"), fps, im.size)

    for i in range(len(img_array)):
        out.write(img_array[i])
    out.release()
    im.close()


def do_analysis(a_path, video_path, mode):
    path = video_path
    os.path.split(path)
    tur = os.path.split(path)
    name = tur[len(tur) - 1].split('.')[0]
    if not os.path.exists("./cap_file/" + name):
        os.mkdir("./cap_file/" + name)
        # ticks=time.time()
    source_npy_side = a_path
    output = open("./cap_file/" + name + "/file2" + ".txt", "w")
    output.close()
    result = {}
    p = './capture_image/' + name + "/"
    lenF = int(len(glob.glob(p + '*.png')) / 2)
    # 对每一张图片的body_25点数据进行分析
    for i in range(1, lenF):  # run_openpose_for_normal(i)
        if (mode == "jump"):
            result_side = analyse_npy_side_jump(name, i, source_npy_side.format(i))
        elif (mode == "pingban"):
            result_side = analyse_npy_side_pingban(name, i, source_npy_side.format(i))
        elif (mode == "juanfu"):
            result_side = analyse_npy_side_juanfu(name, i, source_npy_side.format(i))
        elif (mode == "gaotaitui"):
            result_side = analyse_npy_side_gaotaitui(name, i, source_npy_side.format(i))
        elif (mode == "shendun"):
            result_side = analyse_npy_side_shendun(name, i, source_npy_side.format(i))

        if (result_side != False):
            result[i] = result_side
            # print(result[i])

    output = open("./cap_file/" + name + "/file1.txt", "w")
    for re in result:
        print(re, file=output)
        for (name, value) in result[re].items():
            print(name, value, sep=',', file=output)
        print("kv-over", file=output)
    output.close()


def read2(fileName="./cap_file/file1.txt"):
    file = open(fileName)
    db = {}
    key = file.readline().strip()

    while (key != "kv-over\n"):
        if not key:
            break
        person = {}
        field = file.readline().strip()
        while field != "kv-over":
            name, value = field.split(",")
            person[name] = value.strip()
            field = file.readline().strip()
            if (field == "kv-over\n"):
                break
        db[key] = person
        key = file.readline().strip()
    print("db==== ", db)
    return db


def ignore_data_pingban(result):
    result_ig = result
    k = "0"
    last = {}
    max_index = 1
    for re in result:
        if k == "0":
            k = re
        else:
            if (max_index < int(re)):
                max_index = int(re)

    max_angle = abs(float(result_ig[k]["s_e_angle"]) - float(result_ig[k]["e_w_angle"]))
    max_num = int(k)

    less_angle = 100
    less_num = 1

    max_less_a = 1
    max_less_num = k

    for i in result_ig:
        if (int(i) >= max_index / 3 and int(i) <= max_index / 3 * 2):
            val = math.fabs(
                math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(float(result_ig[i]["knee_ankle_angle"])))
            an_ = abs(float(result_ig[i]["s_e_angle"]) - float(result_ig[i]["e_w_angle"]))
            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
                    float(result_ig[i]["knee_ankle_angle"]))) < less_angle):
                less_angle = val
                less_num = int(i)
            if (an_ < max_angle):
                max_angle = an_
                max_num = i
            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
                    float(result_ig[i]["knee_ankle_angle"]))) > max_less_a):
                max_less_an = val
                max_less_num = int(i)
    re = {}
    re["1"] = {}
    re["1"]["num"] = max_num
    re["1"]["val"] = max_angle
    re["2"] = {}
    re["2"]["num"] = less_num
    re["2"]["val"] = less_angle
    re["3"] = {}
    re["3"]["num"] = max_less_num
    re["3"]["val"] = max_less_a
    # 1表示手肘和肩膀最小角度
    # 2表示最小的身体角度差
    # 3表示最大的身体角度差
    # 1用来说明手部力量 3-2说明稳定性 2说明最好的状态 3说明最差的状态
    print(re)
    return result_ig, re


def ignore_data_juanfu(result):
    result_ig = result
    k = "0"
    last = {}
    max_index = 1
    for re in result:
        if k == "0":
            k = re
        else:
            if (max_index < int(re)):
                max_index = int(re)

    max_angle = result[k]["nose_neck_angle"]
    max_num = int(k)

    less_h_k_a = result[k]["hip_knee_angle"]
    less_h_k_num = k

    max_h_k_a = result[k]["hip_knee_angle"]
    max_h_k_num = k

    less_k_a_a = result[k]["knee_ankle_angle"]
    less_k_a_num = k

    max_k_a_a = result[k]["knee_ankle_angle"]
    max_k_a_num = k

    max_neck_hip_a = result[k]["neck_hip_angle"]
    max_neck_hip_num = k

    for i in result_ig:
        if (float(result_ig[i]["nose_neck_angle"]) > float(max_angle)):
            max_num = int(i)
            max_angle = result_ig[i]["nose_neck_angle"]

        if (float(result_ig[i]["hip_knee_angle"]) > float(max_h_k_a)):
            max_h_k_num = int(i)
            max_h_k_a = result_ig[i]["hip_knee_angle"]

        if (float(result_ig[i]["knee_ankle_angle"]) > float(max_k_a_a)):
            max_k_a_num = int(i)
            max_k_a_a = result_ig[i]["knee_ankle_angle"]

        if (float(result_ig[i]["neck_hip_angle"]) > float(max_neck_hip_a)):
            max_neck_hip_num = int(i)
            max_neck_hip_a = result_ig[i]["neck_hip_angle"]

        if (float(result_ig[i]["hip_knee_angle"]) < float(less_h_k_a)):
            less_h_k_num = int(i)
            less_h_k_a = result_ig[i]["hip_knee_angle"]

        if (float(result_ig[i]["knee_ankle_angle"]) < float(less_k_a_a)):
            less_k_a_num = int(i)
            less_k_a_a = result_ig[i]["knee_ankle_angle"]

    re = {}
    re["1"] = {}
    re["1"]["num"] = max_num
    re["1"]["val"] = max_angle
    re["2"] = {}
    re["2"]["num"] = max_neck_hip_num
    re["2"]["val"] = max_neck_hip_a
    re["3"] = {}
    re["3"]["num"] = float(max_h_k_a) - float(less_h_k_a)
    re["3"]["num1"] = max_h_k_num
    re["3"]["num2"] = less_h_k_num
    re["3"]["val1"] = max_h_k_a
    re["3"]["val2"] = less_h_k_a
    re["4"] = {}
    re["4"]["num"] = float(max_k_a_a) - float(less_k_a_a)
    re["4"]["num1"] = max_k_a_num
    re["4"]["num2"] = less_k_a_num
    re["4"]["val1"] = max_k_a_a
    re["4"]["val2"] = less_k_a_a
    # 1表示头部和脖子角度
    # 2表示脖子和臀部角度
    # 3表示hip-knee的极差 稳定性
    # 4表示knee-ankle的极差 稳定性
    # 3的数据误差太大 待用性待考察
    print(re)
    return result_ig, re


def ignore_data_gaotaitui(result):
    result_ig = result
    k = "0"
    last = {}
    max_index = 1
    for re in result:
        if k == "0":
            k = re
        else:
            if (max_index < int(re)):
                max_index = int(re)
    print("ignore_data_gaotaitui--------")
    print(k)

    max_leg_knee_r_angle = result_ig[k]["knee_ankle_r_angle"]
    max_leg_knee_l_angle = result_ig[k]["knee_ankle_l_angle"]
    max_leg_knee_angle_num = int(k)
    panduan = {}
    for i in result_ig:
        if (float(result_ig[i]["l_d"]) < 30):
            if (float(result_ig[i]["knee_ankle_r_angle"]) < 60 and float(result_ig[i]["hip_knee_r_angle"]) > 120):
                panduan[i] = result_ig[i]["r_d"]
    f = 0
    # ma=0
    print("panduan-----------")
    print(panduan)
    ma = panduan[k]
    key_k = k
    for key in panduan:
        if f == 0:
            ma = panduan[key]
            f = 1
            key_k = key
        elif float(ma) > float(panduan[key]):
            key_k = key
            ma = panduan[key]

    re = {}
    re["1"] = {}
    re["1"]["num"] = key_k
    re["1"]["val"] = ma
    re["1"]["hip_knee_r_angle"] = result_ig[key_k]["hip_knee_r_angle"]
    re["1"]["knee_ankle_r_angle"] = result_ig[key_k]["knee_ankle_r_angle"]

    return result_ig, re


def ignore_data_jump(result):
    print("ignore_data_jump")
    print(result)
    result_ig = result
    k = "0"
    last = {}
    max_index = 1
    for re in result:
        if k == "0":
            k = re
        else:
            if (max_index < int(re)):
                max_index = int(re)

    max_leg_knee_angle = result_ig[k]["knee_ankle_angle"]
    max_leg_knee_angle_num = int(k)
    less_angle = 100
    less_num = 1
    ankle = result_ig[k]["leg_heigh"]
    ankle_num = int(k)
    max_leg_knee_hip_knee = math.fabs(float(result_ig[k]["hip_knee_angle"]) - float(result_ig[k]["knee_ankle_angle"]))
    max_l_h_num = 1
    hip_hei_init = float(result_ig[k]["hip_heigh"])
    # print("max")
    # print(max_index)
    # print(hip_hei_init)

    for i in result_ig:
        if int(i) <= max_index / 5:
            if float(max_leg_knee_angle) < float(result_ig[i]["knee_ankle_angle"]):
                max_leg_knee_angle_num = int(i)
                max_leg_knee_angle = result_ig[i]["knee_ankle_angle"]
        if int(i) <= max_index / 2 and int(i) > max_index / 3:
            val = math.fabs(
                math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(float(result_ig[i]["knee_ankle_angle"])))
            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
                    float(result_ig[i]["knee_ankle_angle"]))) < less_angle):
                less_angle = val
                less_num = int(i)

        if int(i) <= max_index and int(i) > (max_index / 3):

            if (float(result_ig[i]["hip_heigh"])) < (float(hip_hei_init)) and max_l_h_num != 1:
                break
            if (math.fabs(math.fabs(float(result_ig[i]["hip_knee_angle"])) - math.fabs(
                    float(result_ig[i]["knee_ankle_angle"])))) > max_leg_knee_hip_knee and math.fabs(
                float(result_ig[i]["leg_heigh"]) - float(ankle)) <= 20:
                max_leg_knee_hip_knee = math.fabs(
                    float(result_ig[i]["hip_knee_angle"]) - math.fabs(float(result_ig[i]["knee_ankle_angle"])))
                max_l_h_num = int(i)

            #    ankle=result_ig[i]["leg_heigh"]
            #    ankle_num=int(i)
            # elif ankle!=1 and int(i)>=(le/3*2):
            #    break

    print(max_leg_knee_angle)
    print(max_leg_knee_angle_num)
    print(less_num)
    print(less_angle)
    # print(ankle)
    # print(ankle_num)
    print(max_leg_knee_hip_knee)
    print(max_l_h_num)
    re = {}
    re["1"] = {}
    re["1"]["num"] = max_leg_knee_angle_num
    re["1"]["val"] = max_leg_knee_angle
    re["2"] = {}
    re["2"]["num"] = less_num
    re["2"]["val"] = less_angle
    re["3"] = {}
    re["3"]["num"] = max_l_h_num
    re["3"]["val"] = max_leg_knee_hip_knee
    print(re)

    return result_ig, re


def ignore_data_shendun(result):
    result_ig = result
    k = "0"
    last = {}
    max_index = 1
    for re in result:
        if k == "0":
            k = re
        else:
            if (max_index < int(re)):
                max_index = int(re)

    max_d_num = k
    max_d = result[k]["r_d"]
    for i in result_ig:
        if (float(result_ig[i]["r_d"]) > float(max_d)):
            max_d_num = int(i)
            max_d = result_ig[i]["r_d"]

    re = {}
    re["1"] = {}
    re["1"]["num"] = max_d_num
    re["1"]["val"] = max_d

    # 1最大的深蹲角度
    return result_ig, re


def write1(result, name):
    output = open(name, "w")
    for re in result:
        print(re, file=output)
        for (name, value) in result[re].items():
            print(name, value, sep=',', file=output)
        print("kv-over", file=output)
    output.close()
    return name


def run(video_path, mode, need_split):
    path = video_path
    os.path.split(path)
    tur = os.path.split(path)
    name = tur[len(tur) - 1].split('.')[0]
    if (need_split == 1):
        c = split_video(video_path)
        process_photo(name, c)
        gather_video(video_path)
    do_analysis("./capture_image/" + name + "/capture_image{}-1.png.npy", video_path, mode)

    switch = {'jump': ignore_data_jump,  # 注意此处不要加括号
              'pingban': ignore_data_pingban,
              'juanfu': ignore_data_juanfu,
              'shendun': ignore_data_shendun,
              'gaotaitui': ignore_data_gaotaitui,
              }
    choice = mode  # 获取选择
    result, re = switch.get(choice, ignore_data_jump)(read2("./cap_file/" + name + "/file1.txt"))
    # 执行对应的函数，如果没有就执行默认的函数
    # result,re=ignore_data_juanfu(read2("./cap_file/"+name+"/file1.txt"))
    write1(result, "./cap_file/" + name + "/file3.txt")
    write1(re, "./cap_file/" + name + "-file.txt")
    # write1()
    return re


if __name__ == '__main__':
    video_path = "./video/43.mp4"
    # path=video_path
    # os.path.split(path)
    # tur=os.path.split(path)
    # name=tur[len(tur)-1].split('.')[0]

    # c=split_video(video_path)
    # process_photo(name,c)
    # gather_video(video_path)
    # do_analysis("./capture_image/"+name+"/capture_image{}-1.png.npy",video_path,"shendun")
    # result,re=ignore_data_shendun(read2("./cap_file/"+name+"/file1.txt"))
    # write1(result,"./cap_file/"+name+"/file3.txt")
    # write1(re,"./cap_file/"+name+"-file.txt")
    # write1()
    # print(re)
    # re = run(video_path, "juanfu", 1)
    # 参数一 video_path
    # 参数二 shendun jump gaotaitui juanfu pingban
    # 第三个参数为1 表示需要视频切割