import os import random import threading from urllib.parse import urlparse from tqdm import tqdm from Util import ConfigUtil from Util.AesUtil import * from Util.ComfyUIUtil import * from Util.CommonUtil import * from Util.Logger import Logger from Util.OssUtil import uploadOss from Util.PngUtil import * # 定义三种模式 MS_RELAX = 'relax' MS_FAST = 'fast' MS_TURBO = 'turbo' # 获取指定任务号的完成情况 def get_task_info(api_token, result_id): # 获取任务结果 url = "https://goapi.gptnb.me/mj/task/" + str(result_id) + "/fetch" payload = {} headers = { 'Authorization': 'Bearer ' + api_token } # 国内网址，不使用代理 res = requests.request("GET", url, headers=headers, data=payload) # 获取任务结果 return json.loads(res.text) # 下载Midjourney生成的图片，外网地址，需要用VPN挂代理下载 def down_mj_img(image_url, file_path): # 拆分目录和文件名 directory = os.path.dirname(file_path) # 检查目录是否存在 if not os.path.exists(directory): # 如果目录不存在，则创建它 os.makedirs(directory) while True: try: # 使用代理进行下载 response = requests.get(image_url, proxies=proxies) # 获取文件总大小 total_size_in_bytes = int(response.headers.get('content-length', 0)) log.info("开始下载文件，文件大小:" + str(round(total_size_in_bytes / 1024 / 1024, 2)) + "MB") # 创建一个进度条 progress_bar = tqdm(total=total_size_in_bytes, unit='iB', unit_scale=True) # 定义一个函数来处理数据块 def callback_chunk(chunk): progress_bar.update(len(chunk)) # 打开一个本地文件用于写入 with open(file_path, 'wb') as file: # 迭代响应内容 for chunk in response.iter_content(chunk_size=1024): file.write(chunk) callback_chunk(chunk) # 更新进度条 # 关闭进度条 progress_bar.close() # log.info("恭喜，文件下载完成!") break except Exception as err: log.error("发现网络异常，将休息2秒后再试,详细错误信息：" + str(err)) time.sleep(2) # 根据任务编号下载生成的图片 def try_down_mj_img(api_token, task_id, file_path): jo = get_task_info(api_token=api_token, result_id=task_id) # 图片生成情况 if jo['progress'] == '100%' and len(jo['imageUrl']) > 0: image_url = jo['imageUrl'] down_mj_img(image_url, file_path) return 1, '生成完毕！' elif jo['progress'] == '100%' and len(jo['imageUrl']) == 0: return -1, "生成失败，需要重新生成" + jo['failReason'] else: return 0, "没生成完！progress = " + jo['progress'] # 创建图片 def imagine(api_server, api_token, prompt, type_code=MS_RELAX, input_img=None): # 地址 if type_code == MS_RELAX: url = api_server + "/mj-relax/mj/submit/imagine" # relax elif type_code == MS_FAST: url = api_server + "/mj/submit/imagine" # fast elif type_code == MS_TURBO: url = api_server + "/mj-turbo/mj/submit/imagine" # turbo data = { "botType": "MID_JOURNEY", "prompt": prompt, "base64Array": [] } # 垫图转为base64 if input_img is not None: for e in input_img.split(','): img_base64_str = get_image_base64_str(e) data["base64Array"].append(img_base64_str) headers = { 'content-type': 'application/json', 'Authorization': 'Bearer ' + api_token } # 提交的是国内的站点，不需要代理 res = requests.request("POST", url, headers=headers, data=json.dumps(data)) return json.loads(res.text) # 检查指定的风格与形态图是不是存在 def checkStylePoseIdExists(user_id, model_id, style_id, pose_id): # 需要调用远程WEB SERVER的接口，获取是不是此用户+此模型+此风格+此姿势的记录 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/checkStylePoseIdExists' # 要发送的数据，可以是字典形式 data = { 'enData': enData, 'user_id': user_id, 'model_id': model_id, 'style_id': style_id, 'pose_id': pose_id } # 发送GET请求 response = requests.get(url, data=data) # 检查请求是否成功 if response.status_code == 200: exists = json.loads(response.text)['success'] else: log.error('获取用户模型风格与姿势是否存在失败，状态码：', response.status_code) return False return exists # 回写数据库样式与姿势键值对 def record_style_pose_id(user_id, model_id, style_id, pose_id): if not checkStylePoseIdExists(user_id, model_id, style_id, pose_id): # 需要调用远程WEB SERVER的接口，获取是不是此用户+此模型+此风格+此姿势的记录 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/record_style_pose_id' # 要发送的数据，可以是字典形式 data = { 'enData': enData, 'user_id': user_id, 'model_id': model_id, 'style_id': style_id, 'pose_id': pose_id } # 发送GET请求 response = requests.post(url, data=data) # 检查请求是否成功 if response.status_code == 200: log.error('设置用户模型风格与姿势时成功!') else: log.error('设置用户模型风格与姿势时失败，状态码：', response.status_code) # 获取Model对象 def getModel(model_id): file_name = r'JSON/' + str(model_id) + '.json' # 打开JSON文件 if not os.path.exists(file_name): log.error("文件：" + file_name + "不存在，跳过！") return with open(file_name, 'r', encoding='utf-8') as file: data = json.load(file) return data # 获取模型名称 def getModelName(): return data['override_settings']['sd_model_checkpoint'] # 整体的生成任务 def runWebUI(model_id, task_type_code, input_image, total_tasks, user_id, prompt): global data data = getModel(model_id) # data是全局变量 # 生成多少张 data['batch_size'] = total_tasks # 图片 args = data['alwayson_scripts']['ControlNet']['args'] pose_image = data['pose_image'] args[0]['input_image'] = encode_image(input_image[0]) # 如果有特殊的姿态要求,那就用模板指定的姿态图 if len(pose_image) > 0: if len(args) > 1: args[1]['input_image'] = encode_image(pose_image) else: # 如果没有特殊的姿态要求，那么就统一用一张图片 if len(args) > 1: args[1]['input_image'] = encode_image(input_image[0]) # 宽度与高度 width = data['width'] height = data['height'] # 提示词 data['prompt'] = prompt # 开始生成图片 log.info("开始生成图片...") # 设置目标文件夹 target_folder = "Out" # 创建以当前日期命名的目录 folder = os.path.join(target_folder, 'Images/' + task_type_code + "/" + str(model_id) + '/') if not os.path.exists(folder): os.makedirs(folder) # 调用生图服务 response = submit_post(txt2img_url, data) # 保存为图片 for i in range(0, total_tasks): # 创建文件名 png_file = str(uuid.uuid4()) + '.png' # 创建文件的完整路径 file_path = os.path.join(folder, png_file) save_encoded_image(response.json()['images'][i], file_path) # 清除Exif信息 clearExif(file_path, file_path) # 清除Exif信息 # 上传到OSS key = 'Images/' + task_type_code + "/" + str(model_id) + '/' + png_file uploadOss(key, file_path) # # 生成下载链接 url = 'http://hzkc.oss-cn-beijing.aliyuncs.com/' + key # 生成预览链接 # previewSuffix = '?x-oss-process=image/resize,w_150,limit_0' # 删除本地文件 os.remove(file_path) log.info("成功生成第" + str(i + 1) + "张图片,宽度：" + str(width) + ",高度:" + str(height) + " 地址：" + url) # 添加到结果集合中 res.append(url) log.info("本轮图片生成成功, 共完成" + str(total_tasks) + "张图片") def download_image(image_url, file_path): # 发送GET请求 response = requests.get(image_url) # 检查请求是否成功 if response.status_code == 200: # 打开一个文件用于写入 with open(file_path, 'wb') as f: # 将响应的内容写入文件中 f.write(response.content) else: log.error('图片下载失败，状态码：', response.status_code) def generate_random_number(length): return ''.join(random.choices('0123456789', k=length)) # 指定目录下有多少个指定前缀的文件 def getPrefixFileCount(directory_path, prefix): # 使用os.listdir()获取目录下的所有文件和文件夹 entries = os.listdir(directory_path) # 使用os.path.isfile()检查每个条目是否是文件 files = [entry for entry in entries if os.path.isfile(os.path.join(directory_path, entry))] cnt = 0 for file in files: if file.startswith(prefix): cnt = cnt + 1 return cnt def getMyFilter(prompt_data): myfilter = [] # 遍历prompt_data中的所有节点 for key, value in prompt_data.items(): if 'inputs' in value: if 'filename_prefix' in value['inputs']: if value['inputs']['filename_prefix'] == 'ComfyUI': myfilter.append(key) return myfilter def C16(prompt_data, img, model_id, user_id, prompt): # 图生图 prompt_data["22"]["inputs"]["image"] = img[0] # 替换关键词 prompt_data["331"]["inputs"]["text"] = prompt # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C17(prompt_data, img, model_id, user_id, prompt): # 上传姿势 # random_number = random.randint(1, 9) # 9张姿势图 # input_image_pose = './Image/C17/' + str(random_number) + '.png' input_image_pose = './Image/C17/1.jpg' with open(input_image_pose, "rb") as f: imgPose = upload_file(server_address, f, "", True) # 图生图 prompt_data["331"]["inputs"]["image"] = imgPose prompt_data["432"]["inputs"]["image"] = img[0] # 指定数字长度，例如16位 number_length = 16 random_number = generate_random_number(number_length) prompt_data["354"]["inputs"]["seed"] = random_number random_number = generate_random_number(number_length) prompt_data["425"]["inputs"]["seed"] = random_number # 替换关键词 prompt_data["331"]["inputs"]["text"] = prompt # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C19(prompt_data, img, model_id, user_id, prompt): # prompt_data["12"]["inputs"]["image"] = img[0] if len(img) > 1: prompt_data["27"]["inputs"]["image"] = img[1] else: prompt_data["27"]["inputs"]["image"] = img[0] # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C20(prompt_data, img, model_id, user_id, prompt): # prompt_data["12"]["inputs"]["image"] = img[0] if len(img) > 1: prompt_data["27"]["inputs"]["image"] = img[1] else: input_image_style = './Image/C20/meixi.png' # 只上传一张就与梅西握手 with open(input_image_style, "rb") as f: image_style = upload_file(server_address, f, "", True) prompt_data["27"]["inputs"]["image"] = image_style # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C22(prompt_data, img, model_id, user_id, prompt): ####------------------------------------------------------------#### # 记录下用户的风格图+姿势图的组合，下次生成时，尽时避开已经输出过的组合，让用户更好的玩耍 # 获取目录下有多少个pose,多少个style directory_path = './Image/C' + str(model_id) + '/' pose_count = getPrefixFileCount(directory_path, 'pose_') style_count = getPrefixFileCount(directory_path, 'style_') style_id = random.randint(1, style_count) # 查找未使用过的姿态图与姿势图，如果找不到就随机用一个 pose_id = random.randint(1, max(pose_count, 1)) for i in range(1, style_count + 1): for j in range(1, pose_count + 1): if not checkStylePoseIdExists(user_id, model_id, i, j): style_id = i pose_id = j # 回写数据库表，标识这些组合已经用过 record_style_pose_id(user_id, model_id, style_id, pose_id) ####------------------------------------------------------------#### # 风格图 input_image_style = './Image/C' + str(model_id) + '/style_' + str(style_id) + '.png' with open(input_image_style, "rb") as f: image_style = upload_file(server_address, f, "", True) prompt_data["118"]["inputs"]["image"] = image_style # 样式图 input_image_pose = './Image/C' + str(model_id) + '/pose_' + str(pose_id) + '.png' with open(input_image_pose, "rb") as f: image_pose = upload_file(server_address, f, "", True) prompt_data["98"]["inputs"]["image"] = image_pose # 原图 prompt_data["49"]["inputs"]["image"] = img[0] # 提示词 prompt_data["131"]["inputs"]["String"] = prompt # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C23(prompt_data, img, model_id, user_id, prompt): # 原图 prompt_data["52"]["inputs"]["image"] = img[0] # prompt_data["331"]["inputs"]["text"] = prompt # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C24(prompt_data, img, model_id, user_id, prompt): # 原图 prompt_data["12"]["inputs"]["image"] = img[0] # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C25(prompt_data, img, model_id, user_id, prompt): # 原图 prompt_data["111"]["inputs"]["image"] = img[0] ####------------------------------------------------------------#### # 记录下用户的风格图+姿势图的组合，下次生成时，尽时避开已经输出过的组合，让用户更好的玩耍 # 获取目录下有多少个pose,多少个style directory_path = './Image/C' + str(model_id) + '/' pose_count = getPrefixFileCount(directory_path, 'pose_') style_count = getPrefixFileCount(directory_path, 'style_') style_id = random.randint(1, style_count) # 查找未使用过的姿态图与姿势图，如果找不到就随机用一个 pose_id = random.randint(1, max(pose_count, 1)) for i in range(1, style_count + 1): for j in range(1, pose_count + 1): flag = checkStylePoseIdExists(user_id, model_id, i, j) if not flag: style_id = i pose_id = j # 回写数据库表，标识这些组合已经用过 record_style_pose_id(user_id, model_id, style_id, pose_id) ####------------------------------------------------------------#### with open('./Image/C' + str(model_id) + '/style_' + str(style_id) + ".png", "rb") as f: y = upload_file(server_address, f, "", True) # 风格(随机) prompt_data["113"]["inputs"]["image"] = y # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter # 获取C26中有哪些样式 def C26_get_sdxl_styles(): files = ['./JSON/C26/sdxl_styles_sai.json', './JSON/C26/sdxl_styles_twri.json'] SDXL_STYLES = [] for json_file in files: with open(json_file, 'r', encoding="utf-8") as fi: data = json.load(fi) for x in data: SDXL_STYLES.append(x['name']) return SDXL_STYLES def C26(prompt_data, img, model_id, user_id, prompt): # 原图 prompt_data["13"]["inputs"]["image"] = img[0] # 风格图片 SDXL_STYLES = C26_get_sdxl_styles() style_id = random.randint(0, len(SDXL_STYLES) - 1) pose_id = 1 for i in range(0, len(SDXL_STYLES)): if not checkStylePoseIdExists(user_id, model_id, i, 1): style_id = i # 回写数据库表，标识这些组合已经用过 record_style_pose_id(user_id, model_id, style_id, pose_id) prompt_data["79"]["inputs"]["style"] = SDXL_STYLES[style_id] # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def C27(prompt_data, img, model_id, user_id, prompt): # 原图 if len(img) == 1: with open('../Image/huanghai_3.png', "rb") as f: x = upload_file(server_address, f, "", True) prompt_data["82"]["inputs"]["image"] = x prompt_data["78"]["inputs"]["image"] = img[0] # 女 else: prompt_data["13"]["inputs"]["image"] = img[0] # 男 prompt_data["78"]["inputs"]["image"] = img[1] # 女 # 风格图片 style_id = random.randint(1, 2) pose_id = random.randint(1, 3) for i in range(1, 3): for j in range(1, 4): if not checkStylePoseIdExists(user_id, model_id, i, j): style_id = i pose_id = j # 回写数据库表，标识这些组合已经用过 record_style_pose_id(user_id, model_id, style_id, pose_id) # 姿势图有3个 pose_id pose_img_file = './Image/C27/pose_' + str(pose_id) + ".jpg" # 上传姿势图 with open(pose_img_file, "rb") as f: y = upload_file(server_address, f, "", True) prompt_data["82"]["inputs"]["image"] = y # 模型有2个 style_id if style_id == 1: prompt_data["4"]["inputs"]["ckpt_name"] = "samaritan3dCartoon_v40SDXL.safetensors" else: prompt_data["4"]["inputs"]["ckpt_name"] = "turbovisionxlSuperFastXLBasedOnNew_tvxlV431Bakedvae.safetensors" # 过滤器,哪些返回节点中获取到的图片是有用的 myfilter = getMyFilter(prompt_data) return prompt_data, myfilter def runComfyUI(json_file, model_id, task_type_code, input_image, user_id, prompt): # 创建目标目录 output_path = "Out/Images/" + task_type_code + "/" + str(model_id) + "/" if not os.path.exists(output_path): os.makedirs(output_path) # 生成一个唯一的客户端ID client_id = str(uuid.uuid4()) # 上传图片 img = [] for x in input_image: with open(x, "rb") as f: y = upload_file(server_address, f, "", True) img.append(y) with open(json_file, 'r', encoding="utf-8") as fi: prompt_data = json.load(fi) # 调用不同的实现函数 number = json_file[json_file.rfind('/') + 1:-5] # 从最后一个'/'之后开始，到倒数第五个字符结束 # 分支判断 if number == '16': prompt_data, myfilter = C16(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '17': prompt_data, myfilter = C17(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '19': prompt_data, myfilter = C19(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '20': prompt_data, myfilter = C20(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '22': prompt_data, myfilter = C22(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '23': prompt_data, myfilter = C23(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '24': prompt_data, myfilter = C24(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '25': prompt_data, myfilter = C25(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '26': prompt_data, myfilter = C26(prompt_data, img, model_id, user_id, prompt) # 分支判断 if number == '27': prompt_data, myfilter = C27(prompt_data, img, model_id, user_id, prompt) # 生成 files = generate_clip(server_address, prompt_data, client_id, output_path, myfilter) # 上传到云存储，回写数据接口 for file in files: png_file = file + '.png' file_path = './Out/Images/' + task_type_code + "/" + str(model_id) + "/" + png_file # 清除Exif信息 clearExif(file_path, file_path) # 清除Exif信息 # 上传到OSS key = 'Images/' + task_type_code + "/" + str(model_id) + '/' + png_file uploadOss(key, file_path) # # 生成下载链接 url = 'http://hzkc.oss-cn-beijing.aliyuncs.com/' + key res.append(url) # 获取任务 def get_task(): # 获取签名 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/getTask' # 要发送的数据，可以是字典形式 data = { 'enData': enData } # 发送POST请求 response = requests.post(url, data=data) # 检查请求是否成功 if response.status_code == 200: success = response.json()["success"] if success == 1: data = response.json()["data"] # 任务编号 task_id = data['task_id'] # 任务数量 total_count = data["count"] # 用户ID user_id = data['user_id'] # prompt_template 模板内容 prompt_template = data['prompt_template'] # prompt_en prompt_en = data['prompt_en'] if prompt_en is None: prompt_en = '' # 提示词 prompt = prompt_template.replace('{sample}', prompt_en) # 这个返回应该是一个 类似这样的地址： source_img_url = 'http://hzkc.oss-cn-beijing.aliyuncs.com/Images/Upload/wife.jpg',为了扩展支持多张图片上传，所以，多张图片之间用逗号分隔 source_img_url = data["source_img_url"] # 模板ID model_id = data["model_id"] # 任务类型代码 task_type_code = data["task_type_code"] # 模板类型 model_type_id = data["model_type_id"] # 为了扩展支持多张图片，所以这里需要对,号进行拆解 input_image = [] for x in source_img_url.split(','): # 解析URL parsed_url = urlparse(x) # 获取URL路径中的最后一个部分，通常就是文件名 filename = parsed_url.path.split('/')[-1] # 下载这个图片 input_image.append('Temp/' + filename) # input_image扩展为数组，支持多张图片 download_image(x, 'Temp/' + filename) # WEBUI if model_type_id == 1: # 开始生成 log.info("发现需要处理的WebUI任务,task_id=" + str(task_id)) runWebUI(model_id, task_type_code, input_image, total_count, user_id, prompt) # 原来的input_image是单张图片，现在修改为支持多张图片 # COMFY_UI if model_type_id == 2: log.info("发现需要处理的ComfyUI任务,task_id=" + str(task_id)) # 使用哪个文件 json_file = './JSON/' + str(model_id) + '.json' # 请求 runComfyUI(json_file=json_file, model_id=model_id, task_type_code=task_type_code, input_image=input_image, user_id=user_id, prompt=prompt) # Midjourney if model_type_id == 3: log.info("发现需要处理的Midjourney任务...") # 生图 ret = imagine(api_server=ApiServer, api_token=ApiToken, prompt=prompt, type_code=MS_RELAX, input_img=input_image[0]) if ret['code'] == 1: mj_task_id = ret['result'] # 回写WEB服务器数据，表示任务处理中,防止再次被取回来 write_mj_task_id(task_id, mj_task_id) log.info("生图任务创建成功:mj_task_id = " + mj_task_id) else: log.error("生图任务创建生成失败," + str(ret)) return model_type_id, task_id elif success == 0: log.info("现在没有待处理的任务,休息10秒后再试...") return 0, 0 else: message = response.json()["message"] log.warning('发生了异常:' + message) return success else: log.error('请求失败，状态码：', response.status_code) return 0, -1 # 回写MJ任务已发出状态 def write_mj_task_id(task_id, mj_task_id): # 获取签名 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/writeMjTaskId' # 要发送的数据，可以是字典形式 data = { 'task_id': task_id, 'mj_task_id': mj_task_id, 'enData': enData } # 发送POST请求 response = requests.post(url, data=data) # 检查请求是否成功 if response.status_code == 200: log.info("成功完成MJ任务发送状态数据回写！") else: log.error('请求失败，状态码：', response.status_code) # 回复服务器，生图任务完成 def finish_task(task_id, target_img_urls): # 获取签名 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/finishTask' # 要发送的数据，可以是字典形式 data = { 'task_id': task_id, 'enData': enData, 'target_img_urls': target_img_urls } # 发送POST请求 response = requests.post(url, data=data) # 检查请求是否成功 if response.status_code == 200: log.info("成功完成数据回写！") else: log.error('请求失败，状态码：', response.status_code) # 删除云端服务器关于MJ的任务 def delete_mj_task_id(task_id): # 获取签名 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/deleteMjTaskId' # 要发送的数据，可以是字典形式 data = { 'task_id': task_id, 'enData': enData } # 发送POST请求 response = requests.post(url, data=data) # 检查请求是否成功 if response.status_code == 200: log.info("成功完成MJ任务重发！task_id=" + str(task_id)) else: log.error('MJ任务重发请求失败，状态码：', response.status_code) # 后台线程用来跑midjourney的任务 def do_midjourmey(): while True: try: # 获取签名 enData = getenData(machine_id) # 请求的地址 url = web_url + '/QingLong/HuiYa/getMjFetchRecord' # 要发送的数据，可以是字典形式 data = { 'enData': enData, } # 发送GET请求 response = requests.get(url, data=data) # 检查请求是否成功 if response.status_code == 200: jo = json.loads(response.text) if jo['success']: # 绘鸭的任务id task_id = jo['data']['task_id'] # MJ API的任务id mj_task_id = jo['data']['mj_task_id'] # task_type_code task_type_code = jo['data']['task_type_code'] # model_id model_id = jo['data']['model_id'] # 取回来保存的文件名称 file_name = str(uuid.uuid4()) + '.png' file_path = 'Out/Images/' + task_type_code + '/' + str(model_id) + '/' + file_name ret = try_down_mj_img(ApiToken, mj_task_id, file_path) # 图片地址 target_img_urls = '' if ret[0] == 1: dir_path = 'Out/Images/' + task_type_code + '/' + str(model_id) images = split_4_image(file_path, dir_path) for img in images: # 将生成图片上传到OSS key = 'Images/' + task_type_code + "/" + str(model_id) + '/' + img uploadOss(key, os.path.join(dir_path, img)) # # 生成下载链接 url = 'http://hzkc.oss-cn-beijing.aliyuncs.com/' + key target_img_urls = url + ',' + target_img_urls # 删除本地文件 os.remove(os.path.join(dir_path, img)) log.info("成功生成MJ图片,地址：" + url) # 删除4合1图片 os.remove(file_path) # 记录到数据库 target_img_urls = target_img_urls[0:len(target_img_urls) - 1] finish_task(task_id, target_img_urls) elif ret[0] == 0: # 还没有生成完毕 log.info(str(mj_task_id) + " " + ret[1]) time.sleep(3) else: # 生成失败,休息10秒，可能原因：[Queue full] Your job queue is full. Please wait for a job to finish first, then resubmit this one. log.error("【MJ】生成失败，" + ret[1]) time.sleep(20) # 通知云端服务器，此任务需要重新生成 delete_mj_task_id(task_id) else: # log.info("【MJ】没有找到取回来的任务...") time.sleep(3) else: log.error('请求失败，状态码：', response.status_code) except Exception as err: log.error(str(err)) time.sleep(3) if __name__ == '__main__': # 禁止代理 set_http_proxy("") # 配置文件 config = ConfigUtil.getConfig() # 处理机编号 machine_id = config['system']['machine_id'] # 生图服务地址 txt2img_url = config['webui']['txt2img_url'] # WEB服务器地址 web_url = config['webui']['web_url'] # 配置文件 server_address = config.get('comfyui', 'server_address') # 第三方接入TOKEN ApiToken = config['api']['ApiToken'] # 第三方接入服务器的Server地址 ApiServer = config['api']['ApiServer'] # 绘鸭日志文件 LOG = Logger('../Log/HuiYa.log', level='debug') log = LOG.logger # 创建后台线程执行日志记录 thread = threading.Thread(target=do_midjourmey) thread.daemon = True # 设置为后台线程 thread.start() while True: try: res = [] # 所有图片的地址路径 model_type_id, task_id = get_task() # 回复上位生成完毕 if task_id > 0 and model_type_id < 3: # 图片地址 target_img_urls = '' for r in res: target_img_urls = r + ',' + target_img_urls target_img_urls = target_img_urls[0:len(target_img_urls) - 1] finish_task(task_id, target_img_urls) elif task_id == 0: time.sleep(10) except Exception as err: printf("发生异常，将休息10秒后重试..." + str(err)) time.sleep(10)