cleanup

Author: xieyongliang

localizations/zh_CN.json

@@ -292,7 +292,13 @@
     "[wiki]": "[wiki文档]",
     "Embedding": "Embedding",
     "Embedding Learning rate": "Embedding 学习率",
+    "Gradient accumulation steps": "梯度累计步数",
+    "Shuffle tags by ',' when creating prompts.": "创建提示时按“，”打乱标签。",
+    "Drop out tags when creating prompts.": "创建提示时删除标签。",
+    "Choose latent sampling method": "选择隐采样方法",
     "Hypernetwork Learning rate": "Hypernetwork 学习率",
+    "Select activation function of hypernetwork. Recommended : Swish / Linear(none)": "选择 Hypernetwork 的激活函数，推荐Swish / Linear(none)",
+    "Select Layer weights initialization. Recommended: Kaiming for relu-like, Xavier for sigmoid-like, Normal otherwise": "选择图层权重初始化。 推荐：Kaiming 用于 relu-like，Xavier 用于 sigmoid-like，否则为 Normal",
     "Dataset directory": "数据集目录",
     "Log directory": "日志目录",
     "Prompt template file": "提示词模版文件",
@@ -625,17 +631,11 @@
     "Train settings": "训练设置",
     "Train an hypernetwork; you must specify a directory with a set of 1:1 ratio images": "训练 hypernetwork； 必须指定一组具有 1:1 比例图像的目录",
     "Hypernetwork settings": "Hypernetwork 设置",
-    "Sign Options": "登陆选项",
-    "Sign In": "登入",
-    "Sign Up": "注册",
-    "Sign Out": "登出",
     "Username": "用户名",
     "Password": "密码",
-    "Email": "电子邮箱",
-    "Mismatched username/password or not existed username": "用户名/密码不匹配或用户不存在",
-    "Signup failed, please check and retry again": "注册失败，请检查后并重试",
-    "Update failed, please check and retry again": "更新失败，请检查后并重试",
+    "Options": "选项",
     "Output": "输出",
+    "User management (Only available for admin user)": "用户管理 （仅管理员用户可用）",
     "Images S3 URI": "图像 S3 位置",
     "Models S3 URI": "模型 S3 位置",
     "Instance type": "实例类型",
@@ -754,6 +754,25 @@
     "Sample CFG Scale": "采样扩散度",
     "Sample Steps": "采样步数",
     "Cancel": "取消",
+    "Invert colors if your image has white background.": "如果您的图像有白色背景，请反转颜色。 ",
+    "Change your brush width to make it thinner if you want to draw something.": "如果你想画东西，改变你的画笔宽度让它更细。",
+    "Enable": "启用",
+    "Invert Input Color": "反转输入颜色",
+    "RGB to BGR": "RGB 转为 BGR",
+    "Low VRAM": "低 VRAM",
+    "Guess Mode": "猜测模式",
+    "Preprocessor": "预处理器",
+    "Weight": "权重",
+    "Guidance strength (T)": "引导强度 (T)",
+    "Resize Mode": "调整模式",
+    "Envelope (Outer Fit)": "信封（外部适配）",
+    "Scale to Fit (Inner Fit)": "缩放以适合 (内部适配)",
+    "Just Resize": "调整大小",
+    "Canvas Width": "画布宽度",
+    "Canvas Height": "画布高度",
+    "Create blank canvas": "创建空白画布",
+    "Preview annotator result": "预览标注结果",
+    "Hide annotator result": "隐藏标注结果",
 
     "--------": "--------"
 }

localizations/zh_TW.json

@@ -303,7 +303,12 @@
     "[wiki]": "[wiki文件]",
     "Embedding": "Embedding",
     "Embedding Learning rate": "Embedding 學習率",
-    "Hypernetwork Learning rate": "超網路（Hypernetwork）學習率",
+    "Gradient accumulation steps": "梯度累計步數",
+    "Shuffle tags by ',' when creating prompts.": "創建提示時按“，”打亂標籤。",
+    "Drop out tags when creating prompts.": "創建提示時刪除標籤。",
+    "Choose latent sampling method": "選擇隱採樣方法",
+    "Hypernetwork Learning rate": "Hypernetwork 學習率",
+    "Select activation function of hypernetwork. Recommended : Swish / Linear(none)": "選擇 Hypernetwork 的激活函數，推薦Swish / Linear(none)",
     "Learning rate": "學習率",
     "Dataset directory": "資料集目錄",
     "Log directory": "日誌目錄",
@@ -338,7 +343,6 @@
     "End Page": "尾頁",
     "number of images to delete consecutively next": "接下來要連續刪除的圖像數",
     "delete next": "刪除下一張",
-    "Delete": "刪除",
     "sort by": "排序方式",
     "path name": "路徑名",
     "date": "日期",
@@ -489,7 +493,6 @@
     "Check for updates": "檢查更新",
     "Extension": "擴充",
     "URL": "網址",
-    "Update": "更新",
     "a1111-sd-webui-tagcomplete": "標記自動補全",
     "unknown": "未知",
     "deforum-for-automatic1111-webui": "Deforum",
@@ -744,6 +747,25 @@
     "Sample CFG Scale": "採樣擴散度",
     "Sample Steps": "採樣步數",
     "Cancel": "取消",
-    
+    "Invert colors if your image has white background.": "如果您的圖像有白色背景，請反轉顏色。 ",
+    "Change your brush width to make it thinner if you want to draw something.": "如果你想畫東西，改變你的畫筆寬度讓它更細。",
+    "Enable": "啟用",
+    "Invert Input Color": "反轉輸入顏色",
+    "RGB to BGR": "RGB 轉為 BGR",
+    "Low VRAM": "低 VRAM",
+    "Guess Mode": "猜測模式",
+    "Preprocessor": "預處理器",
+    "Weight": "權重",
+    "Guidance strength (T)": "引導強度 (T)",
+    "Resize Mode": "調整模式",
+    "Envelope (Outer Fit)": "信封（外部適配）",
+    "Scale to Fit (Inner Fit)": "縮放以適合 (內部適配)",
+    "Just Resize": "調整大小",
+    "Canvas Width": "畫布寬度",
+    "Canvas Height": "畫布高度",
+    "Create blank canvas": "創建空白畫布",
+    "Preview annotator result": "預覽標註結果",
+    "Hide annotator result": "隱藏標註結果",
+
     "--------": "--------"    
 }

modules/call_queue.py

@@ -18,6 +18,7 @@
 from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops
 
 from modules import shared
+import gradio as gr
 
 queue_lock = threading.Lock()
 
@@ -31,7 +32,7 @@ def f(*args, **kwargs):
 
     return f
 
-def wrap_gradio_gpu_call(func, extra_outputs=None):    
+def wrap_gradio_gpu_call(func, extra_outputs=None):
     def encode_image_to_base64(image):
         if isinstance(image, bytes):
             encoded_string = base64.b64encode(image)
@@ -408,19 +409,16 @@ def sagemaker_inference(task, infer, username, sagemaker_endpoint, *args, **kwar
             info = processed['html_info']
             return images, modules.ui.plaintext_to_html(info), ''
 
-    def f(*args, **kwargs):
+    def f(username, *args, **kwargs):
         if cmd_opts.pureui and func == modules.txt2img.txt2img:
-            username = args[len(args) - 2]
             sagemaker_endpoint = args[len(args) -1]
             args = args[:-2]
             res = sagemaker_inference('text-to-image', 'sync', username, sagemaker_endpoint, *args, **kwargs)
         elif cmd_opts.pureui and func == modules.img2img.img2img:
-            username = args[len(args) - 2]
             sagemaker_endpoint = args[len(args) -1]
             args = args[:-2]
             res = sagemaker_inference('image-to-image', 'sync', username, sagemaker_endpoint, *args, **kwargs)
         elif cmd_opts.pureui and func == modules.extras.run_extras:
-            username = args[len(args) - 2]
             sagemaker_endpoint = args[len(args) -1]
             args = args[:-2]
             res = sagemaker_inference('extras', 'sync', username, sagemaker_endpoint, *args, **kwargs)
@@ -436,14 +434,26 @@ def f(*args, **kwargs):
 
 
 def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
-    def f(*args, extra_outputs_array=extra_outputs, **kwargs):
+    def f(request: gr.Request, *args, extra_outputs_array=extra_outputs, **kwargs):
+        tokens = shared.demo.server_app.tokens
+        cookies = request.headers['cookie'].split('; ')
+        access_token = None
+        for cookie in cookies:
+            if cookie.startswith('access-token'):
+                access_token = cookie[len('access-token=') : ]
+                break
+        username = tokens[access_token]
+
         run_memmon = shared.opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats
         if run_memmon:
             shared.mem_mon.monitor()
         t = time.perf_counter()
 
         try:
-            res = list(func(*args, **kwargs))
+            if func.__name__ == 'f':
+                res = list(func(username, *args, **kwargs))
+            else:
+                res = list(func(*args, **kwargs))
         except Exception as e:
             # When printing out our debug argument list, do not print out more than a MB of text
             max_debug_str_len = 131072 # (1024*1024)/8

modules/sd_models.py

@@ -79,24 +79,27 @@ def modeltitle(path, shorthash):
         return f'{name} [{shorthash}]', shortname
 
     if shared.cmd_opts.pureui:
-        params = {
-            'module': 'Stable-diffusion', 'endpoint_name': sagemaker_endpoint
-        }
-        response = requests.get(url=f'{api_endpoint}/sd/models', params=params)
-        if response.status_code == 200:
-            model_list = json.loads(response.text)
-
-            for model in model_list:
-                h = model['hash']
-                filename = model['filename']
-                title = model['title']
-                short_model_name = model['model_name']
-                config = model['config']
-
-                if 'sd_model_checkpoint' not in shared.opts.data:
-                    shared.opts.data['sd_model_checkpoint'] = title
-
-                checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name, config)
+        if sagemaker_endpoint:
+            params = {
+                'module': 'Stable-diffusion', 'endpoint_name': sagemaker_endpoint
+            }
+            response = requests.get(url=f'{api_endpoint}/sd/models', params=params)
+            if response.status_code == 200:
+                model_list = json.loads(response.text)
+
+                for model in model_list:
+                    h = model['hash']
+                    filename = model['filename']
+                    title = model['title']
+                    short_model_name = model['model_name']
+                    config = model['config']
+
+                    if 'sd_model_checkpoint' not in shared.opts.data:
+                        shared.opts.data['sd_model_checkpoint'] = title
+
+                    checkpoints_list[title] = CheckpointInfo(filename, title, h, short_model_name, config)
+            else:
+                print(response.text)
 
             sd_model_checkpoint = shared.opts.data['sd_model_checkpoint']
             if sd_model_checkpoint and sd_model_checkpoint in checkpoints_list:

modules/shared.py

@@ -144,6 +144,7 @@
     sagemaker_endpoint_component = None
     sd_model_checkpoint_component = None
     create_train_dreambooth_component = None
+    username = ''
 
     response = requests.get(url=f'{api_endpoint}/sd/industrialmodel')
     if response.status_code == 200:
@@ -301,7 +302,9 @@ def list_checkpoint_tiles():
 
 def refresh_checkpoints(sagemaker_endpoint=None):
     import modules.sd_models
-    return modules.sd_models.list_models(sagemaker_endpoint)
+    modules.sd_models.list_models(sagemaker_endpoint)
+    checkpoints = modules.sd_models.checkpoints_list
+    return checkpoints
 
 
 def list_samplers():
@@ -320,7 +323,7 @@ def list_sagemaker_endpoints():
 
     return sagemaker_endpoints
 
-def refresh_sagemaker_endpoints(username=None):
+def refresh_sagemaker_endpoints(username):
     global industrial_model, api_endpoint, sagemaker_endpoints
 
     sagemaker_endpoints = []