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Build error
Build error
Update
Browse files- .pre-commit-config.yaml +35 -0
- .style.yapf +5 -0
- README.md +1 -1
- app.py +61 -92
.pre-commit-config.yaml
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.2.0
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hooks:
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- id: check-executables-have-shebangs
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- id: check-json
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- id: check-merge-conflict
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- id: check-shebang-scripts-are-executable
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- id: check-toml
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- id: check-yaml
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- id: double-quote-string-fixer
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- id: end-of-file-fixer
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- id: mixed-line-ending
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args: ['--fix=lf']
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- id: requirements-txt-fixer
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- id: trailing-whitespace
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- repo: https://github.com/myint/docformatter
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rev: v1.4
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hooks:
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- id: docformatter
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args: ['--in-place']
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- repo: https://github.com/pycqa/isort
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rev: 5.12.0
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hooks:
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- id: isort
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v0.991
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hooks:
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- id: mypy
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args: ['--ignore-missing-imports']
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- repo: https://github.com/google/yapf
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rev: v0.32.0
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hooks:
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- id: yapf
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args: ['--parallel', '--in-place']
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.style.yapf
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[style]
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based_on_style = pep8
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blank_line_before_nested_class_or_def = false
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spaces_before_comment = 2
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split_before_logical_operator = true
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README.md
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@@ -4,7 +4,7 @@ emoji: 🔥
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colorFrom: gray
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colorTo: gray
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sdk: gradio
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sdk_version: 3.
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app_file: app.py
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pinned: false
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---
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colorFrom: gray
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colorTo: gray
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sdk: gradio
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sdk_version: 3.19.1
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app_file: app.py
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pinned: false
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---
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app.py
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from __future__ import annotations
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import argparse
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import functools
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import os
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import pathlib
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import subprocess
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import sys
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import urllib.request
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if os.environ.get('SYSTEM') == 'spaces':
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import mim
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mim.install('mmcv-full==1.
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subprocess.call('pip uninstall -y opencv-python'
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subprocess.call('pip uninstall -y opencv-python-headless'
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subprocess.call(
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subprocess.call('pip install
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subprocess.call('pip install insightface==0.6.2'.split())
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import cv2
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import gradio as gr
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TITLE = 'insightface Face Detection (SCRFD)'
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DESCRIPTION = 'This is an unofficial demo for https://github.com/deepinsight/insightface/tree/master/detection/scrfd.'
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ARTICLE = '<center><img src="https://visitor-badge.glitch.me/badge?page_id=hysts.insightface-scrfd" alt="visitor badge"/></center>'
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TOKEN = os.environ['TOKEN']
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parser = argparse.ArgumentParser()
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parser.add_argument('--face-score-slider-step', type=float, default=0.05)
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parser.add_argument('--face-score-threshold', type=float, default=0.3)
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parser.add_argument('--device', type=str, default='cpu')
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parser.add_argument('--theme', type=str)
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parser.add_argument('--live', action='store_true')
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parser.add_argument('--share', action='store_true')
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parser.add_argument('--port', type=int)
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parser.add_argument('--disable-queue',
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dest='enable_queue',
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action='store_false')
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parser.add_argument('--allow-flagging', type=str, default='never')
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return parser.parse_args()
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def load_model(model_size: str, device) -> nn.Module:
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ckpt_path = huggingface_hub.hf_hub_download(
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'hysts/insightface',
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f'models/scrfd_{model_size}/model.pth',
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use_auth_token=
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scrfd_dir = 'insightface/detection/scrfd'
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config_path = f'{scrfd_dir}/configs/scrfd/scrfd_{model_size}.py'
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model = init_detector(config_path, ckpt_path, device.type)
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pipelines = cfg.data.test.pipeline
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for pipeline in pipelines:
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if pipeline.type == 'MultiScaleFlipAug':
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if mode == 0: #640 scale
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pipeline.img_scale = (640, 640)
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if hasattr(pipeline, 'scale_factor'):
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del pipeline.scale_factor
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elif mode == 1: #for single scale in other pages
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pipeline.img_scale = (1100, 1650)
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if hasattr(pipeline, 'scale_factor'):
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del pipeline.scale_factor
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elif mode == 2: #original scale
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pipeline.img_scale = None
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pipeline.scale_factor = 1.0
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transforms = pipeline.transforms
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@@ -122,64 +107,48 @@ def detect(image: np.ndarray, model_size: str, mode: int,
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return res
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examples=examples,
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title=TITLE,
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description=DESCRIPTION,
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article=ARTICLE,
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theme=args.theme,
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allow_flagging=args.allow_flagging,
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live=args.live,
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).launch(
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enable_queue=args.enable_queue,
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server_port=args.port,
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share=args.share,
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)
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if __name__ == '__main__':
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main()
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from __future__ import annotations
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import functools
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import os
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import pathlib
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import shlex
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import subprocess
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import sys
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import urllib.request
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if os.environ.get('SYSTEM') == 'spaces':
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import mim
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mim.install('mmcv-full==1.4', is_yes=True)
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subprocess.call(shlex.split('pip uninstall -y opencv-python'))
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subprocess.call(shlex.split('pip uninstall -y opencv-python-headless'))
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subprocess.call(
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shlex.split('pip install opencv-python-headless==4.5.5.64'))
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subprocess.call(shlex.split('pip install terminaltables==3.1.0'))
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subprocess.call(shlex.split('pip install mmpycocotools==12.0.3'))
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subprocess.call(shlex.split('pip install insightface==0.6.2'))
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subprocess.call(shlex.split('sed -i 23,26d __init__.py'),
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cwd='insightface/detection/scrfd/mmdet')
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import cv2
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import gradio as gr
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TITLE = 'insightface Face Detection (SCRFD)'
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DESCRIPTION = 'This is an unofficial demo for https://github.com/deepinsight/insightface/tree/master/detection/scrfd.'
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HF_TOKEN = os.getenv('HF_TOKEN')
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def load_model(model_size: str, device) -> nn.Module:
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ckpt_path = huggingface_hub.hf_hub_download(
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'hysts/insightface',
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f'models/scrfd_{model_size}/model.pth',
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use_auth_token=HF_TOKEN)
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scrfd_dir = 'insightface/detection/scrfd'
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config_path = f'{scrfd_dir}/configs/scrfd/scrfd_{model_size}.py'
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model = init_detector(config_path, ckpt_path, device.type)
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pipelines = cfg.data.test.pipeline
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for pipeline in pipelines:
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if pipeline.type == 'MultiScaleFlipAug':
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if mode == 0: # 640 scale
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pipeline.img_scale = (640, 640)
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if hasattr(pipeline, 'scale_factor'):
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del pipeline.scale_factor
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elif mode == 1: # for single scale in other pages
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pipeline.img_scale = (1100, 1650)
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if hasattr(pipeline, 'scale_factor'):
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del pipeline.scale_factor
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elif mode == 2: # original scale
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pipeline.img_scale = None
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pipeline.scale_factor = 1.0
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transforms = pipeline.transforms
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return res
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device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
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model_sizes = [
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'500m',
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'1g',
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'2.5g',
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'10g',
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'34g',
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]
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detectors = {
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model_size: load_model(model_size, device=device)
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for model_size in model_sizes
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}
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modes = [
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'(640, 640)',
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'(1100, 1650)',
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'original',
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]
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func = functools.partial(detect, detectors=detectors)
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image_path = pathlib.Path('selfie.jpg')
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if not image_path.exists():
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url = 'https://raw.githubusercontent.com/peiyunh/tiny/master/data/demo/selfie.jpg'
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urllib.request.urlretrieve(url, image_path)
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examples = [[image_path.as_posix(), '10g', modes[0], 0.3]]
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gr.Interface(
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fn=func,
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inputs=[
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gr.Image(label='Input', type='numpy'),
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gr.Radio(label='Model', choices=model_sizes, type='value',
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value='10g'),
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gr.Radio(label='Mode', choices=modes, type='index', value=modes[0]),
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gr.Slider(label='Face Score Threshold',
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minimum=0,
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maximum=1,
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step=0.05,
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default=0.3),
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],
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outputs=gr.Image(label='Output', type='numpy'),
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examples=examples,
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title=TITLE,
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description=DESCRIPTION,
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).queue().launch(show_api=False)
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