Add files

app.py

@@ -0,0 +1,106 @@
+#!/usr/bin/env python
+
+import mim
+
+mim.uninstall('mmcv-full', confirm_yes=True)
+mim.install('mmcv-full', is_yes=True)
+
+import functools
+import pathlib
+
+import cv2
+import gradio as gr
+import numpy as np
+import PIL.Image
+import torch
+
+import anime_face_detector
+
+
+def detect(img, face_score_threshold: float, landmark_score_threshold: float,
+           detector: anime_face_detector.LandmarkDetector) -> PIL.Image.Image:
+    image = cv2.imread(img.name)
+    preds = detector(image)
+
+    res = image.copy()
+    for pred in preds:
+        box = pred['bbox']
+        box, score = box[:4], box[4]
+        if score < face_score_threshold:
+            continue
+        box = np.round(box).astype(int)
+
+        lt = max(2, int(3 * (box[2:] - box[:2]).max() / 256))
+
+        cv2.rectangle(res, tuple(box[:2]), tuple(box[2:]), (0, 255, 0), lt)
+
+        pred_pts = pred['keypoints']
+        for *pt, score in pred_pts:
+            if score < landmark_score_threshold:
+                color = (0, 255, 255)
+            else:
+                color = (0, 0, 255)
+            pt = np.round(pt).astype(int)
+            cv2.circle(res, tuple(pt), lt, color, cv2.FILLED)
+    res = cv2.cvtColor(res, cv2.COLOR_BGR2RGB)
+
+    image_pil = PIL.Image.fromarray(res)
+    return image_pil
+
+
+def main():
+    sample_path = pathlib.Path('input.jpg')
+    if not sample_path.exists():
+        torch.hub.download_url_to_file(
+            'https://raw.githubusercontent.com/hysts/anime-face-detector/main/assets/input.jpg',
+            sample_path.as_posix())
+
+    detector_name = 'yolov3'
+    device = 'cpu'
+    score_slider_step = 0.05
+    face_score_threshold = 0.5
+    landmark_score_threshold = 0.3
+    live = False
+
+    detector = anime_face_detector.create_detector(detector_name,
+                                                   device=device)
+    func = functools.partial(detect, detector=detector)
+    func = functools.update_wrapper(func, detect)
+
+    title = 'hysts/anime-face-detector'
+    description = 'Demo for hysts/anime-face-detector. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below.'
+    article = "<a href='https://github.com/hysts/anime-face-detector'>GitHub Repo</a>"
+
+    gr.Interface(
+        func,
+        [
+            gr.inputs.Image(type='file', label='Input'),
+            gr.inputs.Slider(0,
+                             1,
+                             step=score_slider_step,
+                             default=face_score_threshold,
+                             label='Face Score Threshold'),
+            gr.inputs.Slider(0,
+                             1,
+                             step=score_slider_step,
+                             default=landmark_score_threshold,
+                             label='Landmark Score Threshold'),
+        ],
+        gr.outputs.Image(type='pil', label='Output'),
+        title=title,
+        description=description,
+        article=article,
+        examples=[
+            [
+                sample_path.as_posix(),
+                face_score_threshold,
+                landmark_score_threshold,
+            ],
+        ],
+        enable_queue=True,
+        live=live,
+    ).launch()
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

@@ -0,0 +1,9 @@
+anime-face-detector>=0.0.4
+mmcv-full>=1.3.16
+mmdet>=2.18.0
+mmpose>=0.20.0
+numpy>=1.21.3
+opencv-python-headless>=4.5.4.58
+openmim>=0.1.5
+torch>=1.10.0
+torchvision>=0.11.1