improve test, add extract to api

client_api/api_utils.py

@@ -8,6 +8,7 @@
 from io import BytesIO
 from typing import List, Tuple, Optional
 import numpy as np
+import requests
 
 
 class InpaintingWhen(Enum):
@@ -151,7 +152,7 @@ class FaceSwapRequest(BaseModel):
 
 class FaceSwapResponse(BaseModel):
     images: List[str] = Field(description="base64 swapped image", default=None)
-    infos: List[str]
+    infos: Optional[List[str]]  # not really used atm
 
     @property
     def pil_images(self) -> Image.Image:
@@ -171,6 +172,23 @@ class FaceSwapCompareRequest(BaseModel):
     )
 
 
+class FaceSwapExtractRequest(BaseModel):
+    images: List[str] = Field(
+        description="base64 reference image",
+        examples=["data:image/jpeg;base64,/9j/4AAQSkZJRgABAQECWAJYAAD...."],
+        default=None,
+    )
+    postprocessing: Optional[PostProcessingOptions]
+
+
+class FaceSwapExtractResponse(BaseModel):
+    images: List[str] = Field(description="base64 face images", default=None)
+
+    @property
+    def pil_images(self) -> Image.Image:
+        return [base64_to_pil(img) for img in self.images]
+
+
 def pil_to_base64(img: Image.Image) -> np.array:  # type:ignore
     if isinstance(img, str):
         img = Image.open(img)
@@ -192,3 +210,20 @@ def base64_to_pil(base64str: Optional[str]) -> Optional[Image.Image]:
         # if no data URL scheme, just decode
         img_bytes = base64.b64decode(base64str)
     return Image.open(io.BytesIO(img_bytes))
+
+
+def compare_faces(
+    image1: Image.Image, image2: Image.Image, base_url: str = "http://localhost:7860"
+) -> float:
+    request = FaceSwapCompareRequest(
+        image1=pil_to_base64(image1),
+        image2=pil_to_base64(image2),
+    )
+
+    result = requests.post(
+        url=f"{base_url}/faceswaplab/compare",
+        data=request.json(),
+        headers={"Content-Type": "application/json; charset=utf-8"},
+    )
+
+    return float(result.text)

client_api/faceswaplab_api_example.py

@@ -7,10 +7,16 @@
     pil_to_base64,
     InpaintingWhen,
     FaceSwapCompareRequest,
+    FaceSwapExtractRequest,
+    FaceSwapExtractResponse,
 )
 
 address = "http://127.0.0.1:7860"
 
+
+#############################
+# FaceSwap
+
 # First face unit :
 unit1 = FaceSwapUnit(
     source_img=pil_to_base64("../references/man.png"),  # The face you want to use
@@ -41,7 +47,7 @@
     image=pil_to_base64("test_image.png"), units=[unit1, unit2], postprocessing=pp
 )
 
-
+# Face Swap
 result = requests.post(
     url=f"{address}/faceswaplab/swap_face",
     data=request.json(),
@@ -52,6 +58,8 @@
 for img in response.pil_images:
     img.show()
 
+#############################
+# Comparison
 
 request = FaceSwapCompareRequest(
     image1=pil_to_base64("../references/man.png"),
@@ -65,3 +73,21 @@
 )
 
 print("similarity", result.text)
+
+#############################
+# Extraction
+
+# Prepare the request
+request = FaceSwapExtractRequest(
+    images=[pil_to_base64(response.pil_images[0])], postprocessing=pp
+)
+
+result = requests.post(
+    url=f"{address}/faceswaplab/extract",
+    data=request.json(),
+    headers={"Content-Type": "application/json; charset=utf-8"},
+)
+response = FaceSwapExtractResponse.parse_obj(result.json())
+
+for img in response.pil_images:
+    img.show()

scripts/faceswaplab.py

@@ -110,7 +110,7 @@ def ui(self, is_img2img: bool) -> List[gr.components.Component]:
             components = []
             for i in range(1, self.units_count + 1):
                 components += faceswaplab_unit_ui.faceswap_unit_ui(is_img2img, i)
-            upscaler = faceswaplab_tab.upscaler_ui()
+            upscaler = faceswaplab_tab.postprocessing_ui()
         # If the order is modified, the before_process should be changed accordingly.
         return components + upscaler
 

scripts/faceswaplab_api/faceswaplab_api.py

@@ -161,3 +161,22 @@ async def compare(
         return swapper.compare_faces(
             base64_to_pil(request.image1), base64_to_pil(request.image2)
         )
+
+    @app.post(
+        "/faceswaplab/extract",
+        tags=["faceswaplab"],
+        description="Extract faces of each images",
+    )
+    async def extract(
+        request: api_utils.FaceSwapExtractRequest,
+    ) -> api_utils.FaceSwapExtractResponse:
+        pp_options = None
+        if request.postprocessing:
+            pp_options = get_postprocessing_options(request.postprocessing)
+        images = [base64_to_pil(img) for img in request.images]
+        faces = swapper.extract_faces(
+            images, extract_path=None, postprocess_options=pp_options
+        )
+        result_images = [encode_to_base64(img) for img in faces]
+        response = api_utils.FaceSwapExtractResponse(images=result_images)
+        return response

scripts/faceswaplab_settings/faceswaplab_settings.py

@@ -41,13 +41,15 @@ def on_ui_settings() -> None:
         "faceswaplab_detection_threshold",
         shared.OptionInfo(
             0.5,
-            "Detection threshold ",
+            "Face Detection threshold",
             gr.Slider,
             {"minimum": 0.1, "maximum": 0.99, "step": 0.001},
             section=section,
         ),
     )
 
+    # DEFAULT UI SETTINGS
+
     shared.opts.add_option(
         "faceswaplab_pp_default_face_restorer",
         shared.OptionInfo(
@@ -105,6 +107,30 @@ def on_ui_settings() -> None:
         ),
     )
 
+    shared.opts.add_option(
+        "faceswaplab_pp_default_inpainting_prompt",
+        shared.OptionInfo(
+            "Portrait of a [gender]",
+            "UI Default inpainting prompt [gender] is replaced by man or woman (requires restart)",
+            gr.Textbox,
+            {},
+            section=section,
+        ),
+    )
+
+    shared.opts.add_option(
+        "faceswaplab_pp_default_inpainting_negative_prompt",
+        shared.OptionInfo(
+            "blurry",
+            "UI Default inpainting negative prompt [gender] (requires restart)",
+            gr.Textbox,
+            {},
+            section=section,
+        ),
+    )
+
+    # UPSCALED SWAPPER
+
     shared.opts.add_option(
         "faceswaplab_upscaled_swapper",
         shared.OptionInfo(

scripts/faceswaplab_swapping/swapper.py

@@ -148,6 +148,71 @@ def batch_process(
     return None
 
 
+def extract_faces(
+    images: List[Image.Image],
+    extract_path: Optional[str],
+    postprocess_options: PostProcessingOptions,
+) -> Optional[List[str]]:
+    """
+    Extracts faces from a list of image files.
+
+    Given a list of image file paths, this function opens each image, extracts the faces,
+    and saves them in a specified directory. Post-processing is applied to each extracted face,
+    and the processed faces are saved as separate PNG files.
+
+    Parameters:
+    files (Optional[List[Image]]): List of file paths to the images to extract faces from.
+    extract_path (Optional[str]): Path where the extracted faces will be saved.
+                                  If no path is provided, a temporary directory will be created.
+    postprocess_options (PostProcessingOptions): Post-processing settings to be applied to the images.
+
+    Returns:
+    Optional[List[img]]: List of face images
+    """
+
+    try:
+        if extract_path:
+            os.makedirs(extract_path, exist_ok=True)
+
+        if images:
+            result_images = []
+            for img in images:
+                faces = get_faces(pil_to_cv2(img))
+
+                if faces:
+                    face_images = []
+                    for face in faces:
+                        bbox = face.bbox.astype(int)
+                        x_min, y_min, x_max, y_max = bbox
+                        face_image = img.crop((x_min, y_min, x_max, y_max))
+
+                        if postprocess_options and (
+                            postprocess_options.face_restorer_name
+                            or postprocess_options.restorer_visibility
+                        ):
+                            postprocess_options.scale = (
+                                1 if face_image.width > 512 else 512 // face_image.width
+                            )
+                            face_image = enhance_image(face_image, postprocess_options)
+
+                        if extract_path:
+                            path = tempfile.NamedTemporaryFile(
+                                delete=False, suffix=".png", dir=extract_path
+                            ).name
+                            face_image.save(path)
+                        face_images.append(face_image)
+
+                    result_images += face_images
+
+            return result_images
+    except Exception as e:
+        logger.info("Failed to extract : %s", e)
+        import traceback
+
+        traceback.print_exc()
+    return None
+
+
 class FaceModelException(Exception):
     """Exception raised when an error is encountered in the face model."""
 

scripts/faceswaplab_ui/faceswaplab_upscaler_ui.py → scripts/faceswaplab_ui/faceswaplab_postprocessing_ui.py

@@ -6,7 +6,7 @@
 from scripts.faceswaplab_postprocessing.postprocessing_options import InpaintingWhen
 
 
-def upscaler_ui() -> List[gr.components.Component]:
+def postprocessing_ui() -> List[gr.components.Component]:
     with gr.Tab(f"Post-Processing"):
         gr.Markdown(
             """Upscaling is performed on the whole image. Upscaling happens before face restoration."""
@@ -87,12 +87,16 @@ def upscaler_ui() -> List[gr.components.Component]:
             )
 
             inpainting_denoising_prompt = gr.Textbox(
-                "Portrait of a [gender]",
+                opts.data.get(
+                    "faceswaplab_pp_default_inpainting_prompt", "Portrait of a [gender]"
+                ),
                 elem_id="faceswaplab_pp_inpainting_denoising_prompt",
                 label="Inpainting prompt use [gender] instead of men or woman",
             )
             inpainting_denoising_negative_prompt = gr.Textbox(
-                "",
+                opts.data.get(
+                    "faceswaplab_pp_default_inpainting_negative_prompt", "blurry"
+                ),
                 elem_id="faceswaplab_pp_inpainting_denoising_neg_prompt",
                 label="Inpainting negative prompt use [gender] instead of men or woman",
             )

scripts/faceswaplab_ui/faceswaplab_tab.py

@@ -1,5 +1,4 @@
 import os
-import tempfile
 from pprint import pformat, pprint
 
 import dill as pickle
@@ -8,14 +7,13 @@
 import onnx
 import pandas as pd
 from scripts.faceswaplab_ui.faceswaplab_unit_ui import faceswap_unit_ui
-from scripts.faceswaplab_ui.faceswaplab_upscaler_ui import upscaler_ui
+from scripts.faceswaplab_ui.faceswaplab_postprocessing_ui import postprocessing_ui
 from insightface.app.common import Face
 from modules import scripts
 from PIL import Image
 from modules.shared import opts
 
 from scripts.faceswaplab_utils import imgutils
-from scripts.faceswaplab_utils.imgutils import pil_to_cv2
 from scripts.faceswaplab_utils.models_utils import get_models
 from scripts.faceswaplab_utils.faceswaplab_logging import logger
 import scripts.faceswaplab_swapping.swapper as swapper
@@ -54,7 +52,7 @@ def extract_faces(
     files: List[gr.File],
     extract_path: Optional[str],
     *components: List[gr.components.Component],
-) -> Optional[List[str]]:
+) -> Optional[List[Image.Image]]:
     """
     Extracts faces from a list of image files.
 
@@ -73,49 +71,13 @@ def extract_faces(
                          If no faces are found, None is returned.
     """
 
-    try:
-        postprocess_options = PostProcessingOptions(*components)  # type: ignore
-
-        if not extract_path:
-            extract_path = tempfile.mkdtemp()
-
-        if files:
-            images = []
-            for file in files:
-                img = Image.open(file.name)
-                faces = swapper.get_faces(pil_to_cv2(img))
-
-                if faces:
-                    face_images = []
-                    for face in faces:
-                        bbox = face.bbox.astype(int)
-                        x_min, y_min, x_max, y_max = bbox
-                        face_image = img.crop((x_min, y_min, x_max, y_max))
-
-                        if (
-                            postprocess_options.face_restorer_name
-                            or postprocess_options.restorer_visibility
-                        ):
-                            postprocess_options.scale = (
-                                1 if face_image.width > 512 else 512 // face_image.width
-                            )
-                            face_image = enhance_image(face_image, postprocess_options)
-
-                        path = tempfile.NamedTemporaryFile(
-                            delete=False, suffix=".png", dir=extract_path
-                        ).name
-                        face_image.save(path)
-                        face_images.append(path)
-
-                    images += face_images
-
-            return images
-    except Exception as e:
-        logger.info("Failed to extract : %s", e)
-        import traceback
-
-        traceback.print_exc()
-    return None
+    postprocess_options = PostProcessingOptions(*components)  # type: ignore
+    images = [
+        Image.open(file.name) for file in files
+    ]  # potentially greedy but Image.open is supposed to be lazy
+    return swapper.extract_faces(
+        images, extract_path=extract_path, postprocess_options=postprocess_options
+    )
 
 
 def analyse_faces(image: Image.Image, det_threshold: float = 0.5) -> Optional[str]:
@@ -459,7 +421,7 @@ def tools_ui() -> None:
         for i in range(1, opts.data.get("faceswaplab_units_count", 3) + 1):
             unit_components += faceswap_unit_ui(False, i, id_prefix="faceswaplab_tab")
 
-    upscale_options = upscaler_ui()
+    upscale_options = postprocessing_ui()
 
     explore_btn.click(
         explore_onnx_faceswap_model, inputs=[model], outputs=[explore_result_text]