3mergeDialogToVideo.py

# rogerxavier-ocr-with-fastapi.hf.space
import os
##这个模型目前只适合确定文本框顺序后再识别,因为如果后面的
##完整图片处理的反例  现在处理的图片是10\0.jpg
# [[[953, 743], [987, 743], [987, 867], [953, 867]], [[917, 745], [951, 745], [951, 867], [917, 867]], [[881, 741], [918, 742], [915, 898], [877, 897]], [[843, 743], [879, 743], [879, 809], [843, 809]], [[629, 1058], [669, 1058], [669, 1210], [629, 1210]], [[549, 1227], [583, 1227], [583, 1381], [549, 1381]], [[535, 115], [563, 115], [563, 145], [535, 145]], [[535, 147], [563, 147], [563, 213], [535, 213]], [[507, 443], [539, 443], [539, 579], [507, 579]], [[505, 115], [533, 115], [533, 197], [505, 197]], [[511, 1225], [547, 1225], [547, 1321], [511, 1321]], [[475, 117], [503, 117], [503, 265], [475, 265]], [[467, 421], [503, 421], [503, 575], [467, 575]], [[419, 235], [447, 235], [447, 337], [419, 337]], [[387, 236], [417, 237], [414, 339], [385, 338]], [[209, 796], [242, 797], [239, 921], [206, 920]], [[175, 173], [205, 173], [205, 225], [175, 225]], [[177, 231], [205, 231], [205, 285], [177, 285]], [[103, 1153], [129, 1153], [129, 1223], [103, 1223]], [[41, 100], [108, 101], [104, 549], [36, 548]]]
# ['就算是你', '没有圣剑', '也不可能有', '胜算', '就算如此', '我也不觉得', '做', ':做个', '·就不觉得', '老好人', '你可怕', '也要有个限度', '我很恐怖吗', '该说真是', '无药可救', '说的是呢', '这个', '但是', '为何?', '第二话让人怜爱']

import requests

import tempfile
import time

from moviepy.audio.AudioClip import AudioArrayClip
from moviepy.editor import *
import cv2
import azure.cognitiveservices.speech as speechsdk
import numpy as np
import io
import base64
import json
from io import BytesIO
import pandas as pd
from PIL import Image
import os
azure_speech_key = os.getenv('azure_speech_key')
azure_service_region = os.getenv('azure_service_region')
my_openai_key = os.getenv('my_openai_key')

print("azure key是",azure_speech_key)
print("azure_service_region是",azure_service_region)
print("my_openai_key",my_openai_key)

#通过去水印完整漫画图片->获取相应的对话框图片->获取对话框文字->返回对话框文字
def get_image_copywrite(image_path:"图片路径(包含后缀)",dialog_cut_path:"对话框切割路径")->"返回漫画关联对话框识别后得到的文案str(原文即可),也可能是none":
    dialog_texts = ''
    associate_dialog_img = get_associate_dialog(image_path=image_path,dialog_cut_path=dialog_cut_path)
    if len(associate_dialog_img)!=0:
        #如果有对应的对话框
        for dialog_img_path in associate_dialog_img:
            cur_dialog_texts = get_sorted_dialog_text(dialog_img_path)#一个对话框的文字list
            if cur_dialog_texts is not None:
                for dialog_text in cur_dialog_texts:
                    dialog_texts += dialog_text
                    dialog_texts += '\n'
            else:
                print(dialog_img_path+"识别是空-可能是有问题")
        return dialog_texts
    return None#不规范图片不请求,直接返回none

#通过传入无水印漫画图片对话框路径,得到关联的对话框图片list
def get_associate_dialog(image_path:"图片路径(包含后缀)",dialog_cut_path:"对话框切割路径")->"返回漫画关联对话框list,也可能是空的list":
    image_name = os.path.splitext(os.path.basename(image_path))[0]
    image_name_format = '{:03d}'.format(int(image_name))

    associated_dialogs = []
    for root, _, files in os.walk(dialog_cut_path):
        for file in files:
            if file.startswith(image_name_format) and file.endswith('.jpg'):
                associated_dialogs.append(os.path.join(root, file))

    return associated_dialogs


#通过对话框图片路径,获取对话框文字list
def get_sorted_dialog_text(image_path:"包含后缀的文件路径")->"返回排序后的text list(一列或者几列话,反正是一个框的内容,几句不清楚,一个框的list当一次文案就行)  或者失败请求返回none":
    image_bytes = open(image_path, 'rb')
    headers = {
        'authority': 'rogerxavier-fastapi-t5-magi.hf.space',
        'scheme': 'https',
        'Accept': '*/*',
        'Accept-Encoding': 'gzip, deflate, br, zstd',
        'Accept-Language': 'zh-CN,zh;q=0.9',
        'Cookie': 'spaces-jwt=eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sIm9uQmVoYWxmT2YiOnsia2luZCI6InVzZXIiLCJfaWQiOiI2NDJhNTNiNTE2ZDRkODI5M2M5YjdiNzgiLCJ1c2VyIjoicm9nZXJ4YXZpZXIifSwiaWF0IjoxNzE2Njg3MzU3LCJzdWIiOiIvc3BhY2VzL3JvZ2VyeGF2aWVyL29jcl93aXRoX2Zhc3RhcGkiLCJleHAiOjE3MTY3NzM3NTcsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ._sGdEgC-ijbIhLmB6iNSBQ_xHNzb4Ydb9mD0L3ByRmJSbB9ccfGbRgtNmkV1JLLldHp_VEKUSQt9Mwq_q4aGAQ',
        'Dnt': '1',
        'Priority': 'u=1, i',
        'Sec-Ch-Ua': '"Chromium";v="124", "Google Chrome";v="124", "Not-A.Brand";v="99"',
        'Sec-Ch-Ua-Mobile': '?0',
        'Sec-Ch-Ua-Platform': '"Windows"',
        'Sec-Fetch-Dest': 'empty',
        'Sec-Fetch-Mode': 'cors',
        'Sec-Fetch-Site': 'same-origin',
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36'
    }
    files = {
        "image": image_bytes,
    }
    try:
        resp = requests.post("https://rogerxavier-ocr-with-fastapi.hf.space/getCoordinates", files=files,headers=headers)#还是有header才能跑
        #先json转换，0为坐标list合集,1为 boxid和text合集
        boxCoordinates , boxInfo = resp.json()[0],resp.json()[1] #分别是list和dict类型

        # 计算文本框的中心点，以便按照从右往左，从上往下的顺序进行排序
        centers = [((box[0][0] + box[2][0]) / 2, (box[0][1] + box[2][1]) / 2) for box in boxCoordinates]

        # 按照中心点的坐标从右往左，从上往下的顺序对文本框坐标进行排序
        sorted_indices = sorted(range(len(centers)), key=lambda i: (-centers[i][0], centers[i][1]))

        # 获取排序后的文本框坐标和对应的文字
        sorted_coordinates = [boxCoordinates[i] for i in sorted_indices]
        sorted_text = [boxInfo['Text'][str(i)] for i in sorted_indices]

        # 根据x方向偏差要求重新排序同一列的文本框
        for i in range(len(sorted_indices) - 1):
            if centers[sorted_indices[i]][0] - centers[sorted_indices[i+1]][0] < (sorted_coordinates[i][2][0] - sorted_coordinates[i][0][0]) / 3:
                if sorted_coordinates[i][0][1] > sorted_coordinates[i+1][2][1]:
                    sorted_indices[i], sorted_indices[i+1] = sorted_indices[i+1], sorted_indices[i]

        sorted_coordinates = [boxCoordinates[i] for i in sorted_indices]
        sorted_text = [boxInfo['Text'][str(i)] for i in sorted_indices]

        print(sorted_coordinates)
        print(sorted_text)
        return sorted_text
    except Exception as e:
        print("图片请求出现问题")
        print(e)
        return None


#通过文字获取音频
def get_audio_data(text:str)-> "返回audio data io句柄, duration":
    # Creates an instance of a speech config with specified subscription key and service region.
    speech_key = azure_speech_key
    service_region = azure_service_region

    speech_config = speechsdk.SpeechConfig(subscription=speech_key, region=service_region)
    # Note: the voice setting will not overwrite the voice element in input SSML.
    speech_config.speech_synthesis_voice_name = "zh-CN-YunxiNeural" ##云希

    # use the default speaker as audio output.
    speech_synthesizer = speechsdk.SpeechSynthesizer(speech_config=speech_config)

    result = speech_synthesizer.speak_text_async(text).get()
    # Check result
    if result.reason == speechsdk.ResultReason.SynthesizingAudioCompleted:
        print("Speech synthesized for text [{}]".format(text))
    elif result.reason == speechsdk.ResultReason.Canceled:
        cancellation_details = result.cancellation_details
        print("Speech synthesis canceled: {}".format(cancellation_details.reason))
        if cancellation_details.reason == speechsdk.CancellationReason.Error:
            print("Error details: {}".format(cancellation_details.error_details))

    # print("音频持续时间是",result.audio_duration)
    # print("音频数据是",result.audio_data)
    # 创建临时文件 -当前路径下面
    with tempfile.NamedTemporaryFile(dir='/',delete=False) as temp_file:
        temp_file.write(result.audio_data)
        temp_file.close()
        # 在这里完成您对文件的操作，比如返回文件名
        file_name = temp_file.name
    return file_name, str(result.audio_duration)


# 补零函数，将数字部分补齐为指定长度
def zero_pad(s, length):
    return s.zfill(length)


def gpt_polish(text:str)->"通过gpt润色str文案并返回str新文案,或者gpt请求失败none":
    # Set your OpenAI API key
    api_key = my_openai_key

    # Define the headers
    headers = {
        'Authorization': f'Bearer {api_key}',
        'Content-Type': 'application/json',
    }

    # Chat Completions request data
    data = {
        'model': 'gpt-3.5-turbo',  # Replace with your chosen model
        'messages': [
            {'role': 'system', 'content': "你是一个assistant,能够根据user发送的漫画中提取的文字,生成一个短视频中一帧的三人称文案(1-2句话)"},
            {'role': 'user', 'content': text}
        ]
    }
    try:

        response = requests.post('https://api.yingwu.lol/v1/chat/completions', headers=headers, data=json.dumps(data))
        print("润色后文案是:"+response.json()['choices'][0]['message']['content'])
        return response.json()['choices'][0]['message']['content']
    except Exception as e:
        print("gpt润色文案失败:")
        print(e)
        return None
if __name__ == '__main__':
    # 获取存放去水印漫画图片的路径 ---放这里是因为获取对话文字时需要和原图关联
    img_path = 'manga1'
    # 获取切割后的文本框路径
    dialog_img_path = 'manga12'

    #获取漫画原图无水印的加入image_files，并排序
    subdir_path = os.path.join(os.getcwd(), img_path)
    # 对话图片经过加入list并补0确定顺序
    image_files = []
    for root, dirs, files in os.walk(subdir_path):
        for file in files:
            if file.endswith(".jpg") or file.endswith(".png"):
                image_files.append(os.path.relpath(os.path.join(root, file)))
    # 对对话框文件名中的数字部分进行补零操作-这样顺序会正常
    image_files.sort(
        key=lambda x: zero_pad(''.join(filter(str.isdigit, os.path.splitext(os.path.basename(x))[0])), 3))

    dialog_subdir_path = os.path.join(os.getcwd(), dialog_img_path)
    # 对话图片经过加入list并补0确定顺序
    dialog_image_files = []
    for root, dirs, files in os.walk(dialog_subdir_path):
        for file in files:
            if file.endswith(".jpg") or file.endswith(".png"):
                dialog_image_files.append(os.path.relpath(os.path.join(root, file)))
    # 对对话框文件名中的数字部分进行补零操作-这样顺序会正常
    dialog_image_files.sort(
        key=lambda x: zero_pad(''.join(filter(str.isdigit, os.path.splitext(os.path.basename(x))[0])), 3))
    # 对话图片经过加入list并补0确定顺序


    ###音视频相关参数-------------------------------------------------------------------------------------
    ##这个是临时生成音频文件的全局变量--方便后续删除
    filename = ''
    # 视频分辨率和帧率
    # 获取第一张图片的尺寸
    image = Image.open(image_files[0])
    width, height = 1125, 1600  # 无法显示可能是win播放器不支持
    fps = 30
    font_path = '1.ttf'  # 设置字体以防默认字体无法同时处理中英文
    # 创建视频编辑器
    video_clips = []
    ###音视频相关参数-------------------------------------------------------------------------------------



    #因为是根据原图无水印的进行遍历,所以处理前要进行筛选，只处理能找到相应对话框图片的原图
    filtered_image_files = []
    for image_path in image_files:
        dialog_list = get_associate_dialog(image_path, dialog_img_path)
        if dialog_list:
            filtered_image_files.append(image_path)

    image_files = filtered_image_files

    for idx, image_file in enumerate(image_files):
        print("现在处理的图片是"+image_file)
        #后面是视音频生成部分-这里图片需要用到完整的去水印的而不是对话框用于识别的
        img = cv2.imread(image_file)
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  ##只支持英文路径

        ##获取当前图片对应的对话框识别文字(还需gpt处理后作为字幕文案)
        cur_copywrite = get_image_copywrite(image_file,dialog_img_path)  # image_file就是6.jpg了
        cur_copywrite = gpt_polish(cur_copywrite)



        if cur_copywrite is not None:

            ##获取当前图片对应的临时音频文件名称和文案时长
            filename, duration = get_audio_data(cur_copywrite)

            clip = ImageClip(img).set_duration(duration).resize((width, height))  # 初始clip

            txt_clip = TextClip(cur_copywrite, fontsize=40, color='white', bg_color='black',
                                font=font_path)  ##文本clip后加入视频

            txt_clip = txt_clip.set_pos(('center', 'bottom')).set_duration(duration)
            # 创建音频剪辑
            audio_clip = AudioFileClip(filename)
            clip = clip.set_audio(audio_clip)  # 将音频与视频片段关联
            clip = CompositeVideoClip([clip, txt_clip])
            video_clips.append(clip)
        else:
            pass  ##图片不规范直接跳过
    video = concatenate_videoclips(video_clips)
    # 保存视频
    video.write_videofile('output_video.mp4', fps=fps)
    # # 在文件关闭后删除临时文件
    print("删除临时mp3文件", filename)
    os.remove(filename)