Update

.gitattributes

@@ -1,22 +1,28 @@
 *.7z filter=lfs diff=lfs merge=lfs -text
 *.arrow filter=lfs diff=lfs merge=lfs -text
 *.bin filter=lfs diff=lfs merge=lfs -text
-*.bin.* filter=lfs diff=lfs merge=lfs -text
 *.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
 *.ftz filter=lfs diff=lfs merge=lfs -text
 *.gz filter=lfs diff=lfs merge=lfs -text
 *.h5 filter=lfs diff=lfs merge=lfs -text
 *.joblib filter=lfs diff=lfs merge=lfs -text
 *.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
 *.model filter=lfs diff=lfs merge=lfs -text
 *.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
 *.onnx filter=lfs diff=lfs merge=lfs -text
 *.ot filter=lfs diff=lfs merge=lfs -text
 *.parquet filter=lfs diff=lfs merge=lfs -text
 *.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
 *.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
 saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.tar.* filter=lfs diff=lfs merge=lfs -text
 *.tflite filter=lfs diff=lfs merge=lfs -text
@@ -24,5 +30,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.wasm filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
-*.zstandard filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

.pre-commit-config.yaml

@@ -0,0 +1,60 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.5.0
+    hooks:
+      - id: check-executables-have-shebangs
+      - id: check-json
+      - id: check-merge-conflict
+      - id: check-shebang-scripts-are-executable
+      - id: check-toml
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+      - id: requirements-txt-fixer
+      - id: trailing-whitespace
+  - repo: https://github.com/myint/docformatter
+    rev: v1.7.5
+    hooks:
+      - id: docformatter
+        args: ["--in-place"]
+  - repo: https://github.com/pycqa/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: v1.8.0
+    hooks:
+      - id: mypy
+        args: ["--ignore-missing-imports"]
+        additional_dependencies:
+          [
+            "types-python-slugify",
+            "types-requests",
+            "types-PyYAML",
+            "types-pytz",
+          ]
+  - repo: https://github.com/psf/black
+    rev: 24.2.0
+    hooks:
+      - id: black
+        language_version: python3.10
+        args: ["--line-length", "119"]
+  - repo: https://github.com/kynan/nbstripout
+    rev: 0.7.1
+    hooks:
+      - id: nbstripout
+        args:
+          [
+            "--extra-keys",
+            "metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
+          ]
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.7.1
+    hooks:
+      - id: nbqa-black
+      - id: nbqa-pyupgrade
+        args: ["--py37-plus"]
+      - id: nbqa-isort
+        args: ["--float-to-top"]

.vscode/settings.json

@@ -0,0 +1,30 @@
+{
+    "editor.formatOnSave": true,
+    "files.insertFinalNewline": false,
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnType": true,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+    },
+    "[jupyter]": {
+        "files.insertFinalNewline": false
+    },
+    "black-formatter.args": [
+        "--line-length=119"
+    ],
+    "isort.args": ["--profile", "black"],
+    "flake8.args": [
+        "--max-line-length=119"
+    ],
+    "ruff.lint.args": [
+        "--line-length=119"
+    ],
+    "notebook.output.scrolling": true,
+    "notebook.formatOnCellExecution": true,
+    "notebook.formatOnSave.enabled": true,
+        "notebook.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
+}

README.md

@@ -4,7 +4,7 @@ emoji: 💩
 colorFrom: red
 colorTo: gray
 sdk: gradio
-sdk_version: 3.0.5
+sdk_version: 4.19.2
 app_file: app.py
 pinned: false
 ---

app.py

@@ -2,8 +2,7 @@
 
 from __future__ import annotations
 
-import argparse
-import functools
+import os
 import pathlib
 import sys
 import urllib.request
@@ -13,49 +12,35 @@ import cv2
 import gradio as gr
 import numpy as np
 import torch
-import torch.nn as nn
 
-sys.path.insert(0, 'face_detection')
+sys.path.insert(0, "face_detection")
 
 from ibug.face_detection import RetinaFacePredictor, S3FDPredictor
 
-TITLE = 'ibug-group/face_detection'
-DESCRIPTION = 'This is an unofficial demo for https://github.com/ibug-group/face_detection.'
-ARTICLE = '<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.ibug-face_detection" alt="visitor badge"/></center>'
-
-
-def parse_args() -> argparse.Namespace:
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--face-score-slider-step', type=float, default=0.05)
-    parser.add_argument('--face-score-threshold', type=float, default=0.8)
-    parser.add_argument('--device', type=str, default='cpu')
-    parser.add_argument('--theme', type=str)
-    parser.add_argument('--live', action='store_true')
-    parser.add_argument('--share', action='store_true')
-    parser.add_argument('--port', type=int)
-    parser.add_argument('--disable-queue',
-                        dest='enable_queue',
-                        action='store_false')
-    parser.add_argument('--allow-flagging', type=str, default='never')
-    return parser.parse_args()
-
-
-def load_model(
-        model_name: str, threshold: float,
-        device: torch.device) -> Union[RetinaFacePredictor, S3FDPredictor]:
-    if model_name == 's3fd':
+DESCRIPTION = "# [ibug-group/face_detection](https://github.com/ibug-group/face_detection)"
+
+
+def load_model(model_name: str, threshold: float, device: torch.device) -> Union[RetinaFacePredictor, S3FDPredictor]:
+    if model_name == "s3fd":
         model = S3FDPredictor(threshold=threshold, device=device)
     else:
-        model_name = model_name.replace('retinaface_', '')
+        model_name = model_name.replace("retinaface_", "")
         model = RetinaFacePredictor(
-            threshold=threshold,
-            device=device,
-            model=RetinaFacePredictor.get_model(model_name))
+            threshold=threshold, device=device, model=RetinaFacePredictor.get_model(model_name)
+        )
     return model
 
 
-def detect(image: np.ndarray, model_name: str, face_score_threshold: float,
-           detectors: dict[str, nn.Module]) -> np.ndarray:
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+model_names = [
+    "retinaface_mobilenet0.25",
+    "retinaface_resnet50",
+    "s3fd",
+]
+detectors = {name: load_model(name, threshold=0.8, device=device) for name in model_names}
+
+
+def detect(image: np.ndarray, model_name: str, face_score_threshold: float) -> np.ndarray:
     model = detectors[model_name]
     model.threshold = face_score_threshold
 
@@ -68,8 +53,7 @@ def detect(image: np.ndarray, model_name: str, face_score_threshold: float,
         box = np.round(pred[:4]).astype(int)
 
         line_width = max(2, int(3 * (box[2:] - box[:2]).max() / 256))
-        cv2.rectangle(res, tuple(box[:2]), tuple(box[2:]), (0, 255, 0),
-                      line_width)
+        cv2.rectangle(res, tuple(box[:2]), tuple(box[2:]), (0, 255, 0), line_width)
 
         if len(pred) == 15:
             pts = pred[5:].reshape(-1, 2)
@@ -79,59 +63,35 @@ def detect(image: np.ndarray, model_name: str, face_score_threshold: float,
     return res[:, :, ::-1]
 
 
-def main():
-    args = parse_args()
-    device = torch.device(args.device)
-
-    model_names = [
-        'retinaface_mobilenet0.25',
-        'retinaface_resnet50',
-        's3fd',
-    ]
-    detectors = {
-        name: load_model(name,
-                         threshold=args.face_score_threshold,
-                         device=device)
-        for name in model_names
-    }
-
-    func = functools.partial(detect, detectors=detectors)
-    func = functools.update_wrapper(func, detect)
-
-    image_path = pathlib.Path('selfie.jpg')
-    if not image_path.exists():
-        url = 'https://raw.githubusercontent.com/peiyunh/tiny/master/data/demo/selfie.jpg'
-        urllib.request.urlretrieve(url, image_path)
-    examples = [[image_path.as_posix(), model_names[1], 0.8]]
-
-    gr.Interface(
-        func,
-        [
-            gr.inputs.Image(type='numpy', label='Input'),
-            gr.inputs.Radio(model_names,
-                            type='value',
-                            default='retinaface_resnet50',
-                            label='Model'),
-            gr.inputs.Slider(0,
-                             1,
-                             step=args.face_score_slider_step,
-                             default=args.face_score_threshold,
-                             label='Face Score Threshold'),
-        ],
-        gr.outputs.Image(type='numpy', label='Output'),
-        examples=examples,
-        title=TITLE,
-        description=DESCRIPTION,
-        article=ARTICLE,
-        theme=args.theme,
-        allow_flagging=args.allow_flagging,
-        live=args.live,
-    ).launch(
-        enable_queue=args.enable_queue,
-        server_port=args.port,
-        share=args.share,
+example_image_path = pathlib.Path("selfie.jpg")
+if not example_image_path.exists():
+    url = "https://raw.githubusercontent.com/peiyunh/tiny/master/data/demo/selfie.jpg"
+    urllib.request.urlretrieve(url, example_image_path)
+
+with gr.Blocks(css="style.css") as demo:
+    gr.Markdown(DESCRIPTION)
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(type="numpy", label="Input")
+            model_name = gr.Radio(model_names, type="value", value="retinaface_resnet50", label="Model")
+            score_threshold = gr.Slider(minimum=0, maximum=1, step=0.05, value=0.8, label="Face Score Threshold")
+            run_button = gr.Button()
+        with gr.Column():
+            result = gr.Image(label="Output")
+    gr.Examples(
+        examples=[[example_image_path.as_posix(), model_names[1], 0.8]],
+        inputs=[image, model_name, score_threshold],
+        outputs=result,
+        fn=detect,
+        cache_examples=os.getenv("CACHE_EXAMPLES") == "1",
+    )
+    run_button.click(
+        fn=detect,
+        inputs=[image, model_name, score_threshold],
+        outputs=result,
+        api_name="detect",
     )
 
 
-if __name__ == '__main__':
-    main()
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()

requirements.txt

@@ -1,4 +1,4 @@
-numpy==1.22.3
-opencv-python-headless==4.5.5.64
-torch==1.11.0
-torchvision==0.12.0
+numpy==1.26.4
+opencv-python-headless==4.9.0.80
+torch==2.0.1
+torchvision==0.15.2

style.css

@@ -0,0 +1,11 @@
+h1 {
+  text-align: center;
+  display: block;
+}
+
+#duplicate-button {
+  margin: auto;
+  color: #fff;
+  background: #1565c0;
+  border-radius: 100vh;
+}