starting from the scratch

README.md

@@ -1,14 +1,29 @@
 ---
 title: FaceFusion
-emoji: 🏢
-colorFrom: red
-colorTo: gray
+emoji: 😻
+colorFrom: purple
+colorTo: green
 sdk: gradio
 sdk_version: 5.49.0
 app_file: app.py
 pinned: false
 license: mit
-short_description: Image face swap
+short_description: Swap faces in images
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## Unofficial FaceFusion Implementation
+
+FaceFusion has evolved significantly, increasing in complexity over time.  
+This project was therefore developed from scratch to provide a simplified and more accessible implementation while retaining the essential functionality.
+
+## Acknowledgments
+
+This work preserves key functionality from the original authors:
+- [DeepInsight](https://github.com/deepinsight/insightface)
+- [FaceFusion](https://github.com/facefusion/facefusion)
+
+## Contact
+
+For questions, comments, or feedback, please contact:  
+📧 **[email protected]**
+

app.py

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+#######################################################################################
+#
+# MIT License
+#
+# Copyright (c) [2025] [[email protected]]
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+#
+#######################################################################################
+#
+# Source code is based on or inspired by several projects.
+# For more details and proper attribution, please refer to the following resources:
+#
+# - [Deepinsight] - [https://github.com/deepinsight/insightface]
+# - [FaceFusion] [https://github.com/facefusion/facefusion]
+#
+
+import gradio as gr
+from huggingface_hub import hf_hub_download
+from itertools import islice
+from face_analysis import FaceAnalysis
+from models.inswapper import INSwapper
+
+REPO_ID = "leonelhs/insightface"
+model_inswapper_path = hf_hub_download(repo_id=REPO_ID, filename="inswapper_128.onnx")
+
+face_analyser = FaceAnalysis()
+swapper = INSwapper(model_inswapper_path)
+
+
+def predict(src_img, dst_img):
+
+    # Get faces
+    src_faces = face_analyser.get(src_img)
+    dst_faces = face_analyser.get(dst_img)
+
+    # Swap the first face found
+    if len(src_faces) > 0 and len(dst_faces) > 0:
+        return dst_img, swapper.get(dst_img, dst_faces[0], src_faces[0], paste_back=True)
+    else:
+        raise gr.Error("No faces were found!")
+
+with gr.Blocks(title="FaceFusion") as app:
+    navbar = gr.Navbar(visible=True, main_page_name="Workspace")
+    gr.Markdown("## FaceFusion Lite")
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Row():
+                source_image = gr.Image(type="numpy", label="Face image")
+                target_image = gr.Image(type="numpy", label="Body image")
+            image_btn = gr.Button("Swap face")
+        with gr.Column(scale=1):
+            with gr.Row():
+                output_image = gr.ImageSlider(label="Swapped image", type="pil")
+    image_btn.click(
+        fn=predict,
+        inputs=[source_image, target_image],
+        outputs=output_image,
+    )
+
+with app.route("Readme", "/readme"):
+    with open("README.md") as f:
+        for line in islice(f, 12, None):
+            gr.Markdown(line.strip())
+
+app.launch(share=False, debug=True, show_error=True, mcp_server=True, pwa=True)
+app.queue()
+
+
+

face_analysis.py

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+# -*- coding: utf-8 -*-
+# @Organization  : insightface.ai
+# @Author        : Jia Guo
+# @Time          : 2021-05-04
+# @Function      : 
+
+
+from __future__ import division
+
+import onnxruntime
+
+__all__ = ['FaceAnalysis']
+
+from utils.common import Face
+from models.arcface_onnx import ArcFaceONNX
+from models.attribute import Attribute
+from models.landmark import Landmark
+from models.retinaface import RetinaFace
+from huggingface_hub import hf_hub_download
+
+REPO_ID = "leonelhs/insightface"
+
+model_detector_path = hf_hub_download(repo_id=REPO_ID, filename="det_10g.onnx")
+model_landmark_3d_68_path = hf_hub_download(repo_id=REPO_ID, filename="1k3d68.onnx")
+model_landmark_2d_106_path = hf_hub_download(repo_id=REPO_ID, filename="2d106det.onnx")
+model_genderage_path = hf_hub_download(repo_id=REPO_ID, filename="genderage.onnx")
+model_recognition_path = hf_hub_download(repo_id=REPO_ID, filename="w600k_r50.onnx")
+
+class FaceAnalysis:
+    def __init__(self):
+        onnxruntime.set_default_logger_severity(3)
+
+        self.detector = RetinaFace(model_file=model_detector_path, input_size=(640, 640), det_thresh=0.5)
+        self.landmark_3d_68 = Landmark(model_file=model_landmark_3d_68_path)
+        self.landmark_2d_106 = Landmark(model_file=model_landmark_2d_106_path)
+        self.genderage = Attribute(model_file=model_genderage_path)
+        self.recognition = ArcFaceONNX(model_file=model_recognition_path)
+
+    def get(self, img, max_num=0):
+        bboxes, kpss = self.detector.detect(img,
+                                            max_num=max_num,
+                                            metric='default')
+        if bboxes.shape[0] == 0:
+            return []
+        ret = []
+        for i in range(bboxes.shape[0]):
+            bbox = bboxes[i, 0:4]
+            det_score = bboxes[i, 4]
+            kps = None
+            if kpss is not None:
+                kps = kpss[i]
+            face = Face(bbox=bbox, kps=kps, det_score=det_score)
+            self.landmark_3d_68.get(img, face)
+            self.landmark_2d_106.get(img, face)
+            self.genderage.get(img, face)
+            self.recognition.get(img, face)
+            ret.append(face)
+        return ret

meanshape_68.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:39ffecf84ba73f0d0d7e49380833ba88713c9fcdec51df4f7ac45a48b8f4cc51
+size 974

playground.py

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+import cv2
+
+from face_analysis import FaceAnalysis
+from models.inswapper import INSwapper
+
+app = FaceAnalysis()
+
+swapper = INSwapper('./inswapper_128.onnx')
+
+source_img = "/home/leonel/Pictures/bun01.jpg"
+target_img = "/home/leonel/Pictures/ac6a1e147711139.62c72d282c159.png"
+
+# Load source and target images
+src_img = cv2.imread(source_img)
+dst_img = cv2.imread(target_img)
+
+# Get faces
+src_faces = app.get(src_img)
+dst_faces = app.get(dst_img)
+
+# Swap the first face found
+if len(src_faces) > 0 and len(dst_faces) > 0:
+    result = swapper.get(dst_img, dst_faces[0], src_faces[0], paste_back=True)
+    cv2.imwrite("swapped2.jpg", result)

requirements.txt

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+numpy~=2.2.6
+opencv-python~=4.12.0.88
+scikit-image~=0.25.2
+onnx~=1.19.0
+onnxruntime~=1.22.1