Update

.pre-commit-config.yaml

@@ -0,0 +1,35 @@
+repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v4.2.0
+  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: double-quote-string-fixer
+  - 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: v1.4
+  hooks:
+  - id: docformatter
+    args: ['--in-place']
+- repo: https://github.com/pycqa/isort
+  rev: 5.12.0
+  hooks:
+    - id: isort
+- repo: https://github.com/pre-commit/mirrors-mypy
+  rev: v0.991
+  hooks:
+    - id: mypy
+      args: ['--ignore-missing-imports']
+- repo: https://github.com/google/yapf
+  rev: v0.32.0
+  hooks:
+  - id: yapf
+    args: ['--parallel', '--in-place']

.style.yapf

@@ -0,0 +1,5 @@
+[style]
+based_on_style = pep8
+blank_line_before_nested_class_or_def = false
+spaces_before_comment = 2
+split_before_logical_operator = true

README.md

@@ -4,7 +4,7 @@ emoji: 🔥
 colorFrom: gray
 colorTo: gray
 sdk: gradio
-sdk_version: 3.0.5
+sdk_version: 3.19.1
 app_file: app.py
 pinned: false
 ---

app.py

@@ -2,26 +2,28 @@
 
 from __future__ import annotations
 
-import argparse
 import functools
 import os
 import pathlib
+import shlex
 import subprocess
 import sys
 import urllib.request
 
 if os.environ.get('SYSTEM') == 'spaces':
     import mim
-    mim.install('mmcv-full==1.3.3', is_yes=True)
+    mim.install('mmcv-full==1.4', is_yes=True)
 
-    subprocess.call('pip uninstall -y opencv-python'.split())
-    subprocess.call('pip uninstall -y opencv-python-headless'.split())
-    subprocess.call('pip install opencv-python-headless==4.5.5.64'.split())
-    subprocess.call('pip install terminaltables==3.1.0'.split())
-    subprocess.call('pip install mmpycocotools==12.0.3'.split())
-
-    subprocess.call('pip install insightface==0.6.2'.split())
+    subprocess.call(shlex.split('pip uninstall -y opencv-python'))
+    subprocess.call(shlex.split('pip uninstall -y opencv-python-headless'))
+    subprocess.call(
+        shlex.split('pip install opencv-python-headless==4.5.5.64'))
+    subprocess.call(shlex.split('pip install terminaltables==3.1.0'))
+    subprocess.call(shlex.split('pip install mmpycocotools==12.0.3'))
 
+    subprocess.call(shlex.split('pip install insightface==0.6.2'))
+    subprocess.call(shlex.split('sed -i 23,26d __init__.py'),
+                    cwd='insightface/detection/scrfd/mmdet')
 
 import cv2
 import gradio as gr
@@ -36,32 +38,15 @@ from mmdet.apis import inference_detector, init_detector, show_result_pyplot
 
 TITLE = 'insightface Face Detection (SCRFD)'
 DESCRIPTION = 'This is an unofficial demo for https://github.com/deepinsight/insightface/tree/master/detection/scrfd.'
-ARTICLE = '<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.insightface-scrfd" alt="visitor badge"/></center>'
-
-TOKEN = os.environ['TOKEN']
-
 
-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=0.3)
-    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()
+HF_TOKEN = os.getenv('HF_TOKEN')
 
 
 def load_model(model_size: str, device) -> nn.Module:
     ckpt_path = huggingface_hub.hf_hub_download(
         'hysts/insightface',
         f'models/scrfd_{model_size}/model.pth',
-        use_auth_token=TOKEN)
+        use_auth_token=HF_TOKEN)
     scrfd_dir = 'insightface/detection/scrfd'
     config_path = f'{scrfd_dir}/configs/scrfd/scrfd_{model_size}.py'
     model = init_detector(config_path, ckpt_path, device.type)
@@ -73,15 +58,15 @@ def update_test_pipeline(model: nn.Module, mode: int):
     pipelines = cfg.data.test.pipeline
     for pipeline in pipelines:
         if pipeline.type == 'MultiScaleFlipAug':
-            if mode == 0:  #640 scale
+            if mode == 0:  # 640 scale
                 pipeline.img_scale = (640, 640)
                 if hasattr(pipeline, 'scale_factor'):
                     del pipeline.scale_factor
-            elif mode == 1:  #for single scale in other pages
+            elif mode == 1:  # for single scale in other pages
                 pipeline.img_scale = (1100, 1650)
                 if hasattr(pipeline, 'scale_factor'):
                     del pipeline.scale_factor
-            elif mode == 2:  #original scale
+            elif mode == 2:  # original scale
                 pipeline.img_scale = None
                 pipeline.scale_factor = 1.0
             transforms = pipeline.transforms
@@ -122,64 +107,48 @@ def detect(image: np.ndarray, model_size: str, mode: int,
     return res
 
 
-def main():
-    args = parse_args()
-    device = torch.device(args.device)
-
-    model_sizes = [
-        '500m',
-        '1g',
-        '2.5g',
-        '10g',
-        '34g',
-    ]
-    detectors = {
-        model_size: load_model(model_size, device=device)
-        for model_size in model_sizes
-    }
-    modes = [
-        '(640, 640)',
-        '(1100, 1650)',
-        'original',
-    ]
-
-    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(), '10g', modes[0], 0.3]]
-
-    gr.Interface(
-        func,
-        [
-            gr.inputs.Image(type='numpy', label='Input'),
-            gr.inputs.Radio(
-                model_sizes, type='value', default='10g', label='Model'),
-            gr.inputs.Radio(
-                modes, type='index', default=modes[0], label='Mode'),
-            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,
-    )
-
-
-if __name__ == '__main__':
-    main()
+device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+
+model_sizes = [
+    '500m',
+    '1g',
+    '2.5g',
+    '10g',
+    '34g',
+]
+detectors = {
+    model_size: load_model(model_size, device=device)
+    for model_size in model_sizes
+}
+modes = [
+    '(640, 640)',
+    '(1100, 1650)',
+    'original',
+]
+
+func = functools.partial(detect, detectors=detectors)
+
+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(), '10g', modes[0], 0.3]]
+
+gr.Interface(
+    fn=func,
+    inputs=[
+        gr.Image(label='Input', type='numpy'),
+        gr.Radio(label='Model', choices=model_sizes, type='value',
+                 value='10g'),
+        gr.Radio(label='Mode', choices=modes, type='index', value=modes[0]),
+        gr.Slider(label='Face Score Threshold',
+                  minimum=0,
+                  maximum=1,
+                  step=0.05,
+                  default=0.3),
+    ],
+    outputs=gr.Image(label='Output', type='numpy'),
+    examples=examples,
+    title=TITLE,
+    description=DESCRIPTION,
+).queue().launch(show_api=False)