UPDATE: API Support is now ready

VersionUP

README.md

@@ -1,6 +1,8 @@
-# NSFW-Roop 0.1.0 for StableDiffusion
+# Roop-GE 0.2.0 for StableDiffusion
 ### NSFW (uncensored) version (use it on your own responsibility) of [original sd-webui-roop](https://github.com/s0md3v/sd-webui-roop) with a lot of improvements
 
+> GE (Gourieff Edition), aka "NSFW-Roop"
+
 This is an extension for StableDiffusion's [AUTOMATIC1111 web-ui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) that allows face-replacement in images. It is based on [Roop-GE](https://github.com/Gourieff/Roop-GE).
 
 <img src="example/demo_crop.jpg" alt="example"/>
@@ -26,9 +28,15 @@ To install the extension, follow these steps:
 
 ## Usage
 
-1. Under "NSFW-Roop" drop-down menu, import an image containing a face.
+1. Under "Roop-GE" drop-down menu, import an image containing a face;
-2. Turn on the "Enable" checkbox
+2. Turn on the "Enable" checkbox;
-3. That's it, now the generated result will have the face you selected
+3. That's it, now the generated result will have the face you selected.
+
+**You can use Roop-GE with Webui API:**
+1. Check the [SD Web API Wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API) for how to use API;
+2. Call `requests.get(url=f'{address}/sdapi/v1/script-info')` to find the args that Roop-GE needs;
+3. Define Roop-GE script args and add like this `"alwayson_scripts": {"roop-ge":{"args":args}}` in the payload;
+4. Call the API, there's an [full usage example](./example/api_example.py) in example folder.
 
 ### The result face is blurry
 Use the "Restore Face" option. You can also try the "Upscaler" option or for more finer control, use an upscaler from the "Extras" tab.

scripts/faceswap.py

@@ -26,13 +26,13 @@ def get_models():
 
 class FaceSwapScript(scripts.Script):
     def title(self):
-        return f"NSFW-Roop"
+        return f"Roop-GE"
 
     def show(self, is_img2img):
         return scripts.AlwaysVisible
 
     def ui(self, is_img2img):
-        with gr.Accordion(f"NSFW-Roop {version_flag}", open=False):
+        with gr.Accordion(f"Roop-GE {version_flag}", open=False):
             with gr.Column():
                 img = gr.inputs.Image(type="pil")
                 enable = gr.Checkbox(False, placeholder="enable", label="Enable")
@@ -179,7 +179,7 @@ class FaceSwapScript(scripts.Script):
         if self.enable:
             if self.source is not None:
                 if isinstance(p, StableDiffusionProcessingImg2Img) and swap_in_source:
-                    logger.info(f"NSFW-Roop is enabled, face index %s", self.faces_index)
+                    logger.info(f"Roop-GE is enabled, face index %s", self.faces_index)
 
                     for i in range(len(p.init_images)):
                         logger.info(f"Swap in source %s", i)

scripts/roop_logging.py

@@ -24,7 +24,7 @@ class ColoredFormatter(logging.Formatter):
 
 
 # Create a new logger
-logger = logging.getLogger("NSFW-Roop")
+logger = logging.getLogger("Roop-GE")
 logger.propagate = False
 
 # Add handler if we don't have one.

scripts/roop_version.py

@@ -1,5 +1,5 @@
-version_flag = "v0.1.0"
+version_flag = "v0.2.0"
 
 from scripts.roop_logging import logger
 
-logger.info(f"NSFW-Roop {version_flag}")
+logger.info(f"Roop-GE {version_flag}")

scripts/swapper.py

@@ -66,7 +66,7 @@ def upscale_image(image: Image, upscale_options: UpscaleOptions):
     if upscale_options.do_restore_first:
         if upscale_options.face_restorer is not None:
             original_image = result_image.copy()
-            logger.info("1. Restore face with %s", upscale_options.face_restorer.name())
+            logger.info("Restore face with %s", upscale_options.face_restorer.name())
             numpy_image = np.array(result_image)
             numpy_image = upscale_options.face_restorer.restore(numpy_image)
             restored_image = Image.fromarray(numpy_image)
@@ -76,7 +76,7 @@ def upscale_image(image: Image, upscale_options: UpscaleOptions):
         if upscale_options.upscaler is not None and upscale_options.upscaler.name != "None":
             original_image = result_image.copy()
             logger.info(
-                "2. Upscale with %s scale = %s",
+                "Upscale with %s scale = %s",
                 upscale_options.upscaler.name,
                 upscale_options.scale,
             )
@@ -91,7 +91,7 @@ def upscale_image(image: Image, upscale_options: UpscaleOptions):
         if upscale_options.upscaler is not None and upscale_options.upscaler.name != "None":
             original_image = result_image.copy()
             logger.info(
-                "1. Upscale with %s scale = %s",
+                "Upscale with %s scale = %s",
                 upscale_options.upscaler.name,
                 upscale_options.scale,
             )
@@ -104,7 +104,7 @@ def upscale_image(image: Image, upscale_options: UpscaleOptions):
                 )
         if upscale_options.face_restorer is not None:
             original_image = result_image.copy()
-            logger.info("2. Restore face with %s", upscale_options.face_restorer.name())
+            logger.info("Restore face with %s", upscale_options.face_restorer.name())
             numpy_image = np.array(result_image)
             numpy_image = upscale_options.face_restorer.restore(numpy_image)
             restored_image = Image.fromarray(numpy_image)
@@ -152,6 +152,20 @@ def swap_face(
     result_image = target_img
     fn = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
     if model is not None:
+
+        if isinstance(source_img, str):  # source_img is a base64 string
+            import base64, io
+            if 'base64,' in source_img:  # check if the base64 string has a data URL scheme
+                # split the base64 string to get the actual base64 encoded image data
+                base64_data = source_img.split('base64,')[-1]
+                # decode base64 string to bytes
+                img_bytes = base64.b64decode(base64_data)
+            else:
+                # if no data URL scheme, just decode
+                img_bytes = base64.b64decode(source_img)
+            
+            source_img = Image.open(io.BytesIO(img_bytes))
+            
         source_img = cv2.cvtColor(np.array(source_img), cv2.COLOR_RGB2BGR)
         target_img = cv2.cvtColor(np.array(target_img), cv2.COLOR_RGB2BGR)
         source_face = get_face_single(source_img, face_index=source_faces_index[0])