hysts HF staff commited on
Commit
bef99af
1 Parent(s): bfe786b
.pre-commit-config.yaml CHANGED
@@ -1,35 +1,60 @@
1
  repos:
2
- - repo: https://github.com/pre-commit/pre-commit-hooks
3
- rev: v4.2.0
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- hooks:
5
- - id: check-executables-have-shebangs
6
- - id: check-json
7
- - id: check-merge-conflict
8
- - id: check-shebang-scripts-are-executable
9
- - id: check-toml
10
- - id: check-yaml
11
- - id: double-quote-string-fixer
12
- - id: end-of-file-fixer
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- - id: mixed-line-ending
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- args: ['--fix=lf']
15
- - id: requirements-txt-fixer
16
- - id: trailing-whitespace
17
- - repo: https://github.com/myint/docformatter
18
- rev: v1.4
19
- hooks:
20
- - id: docformatter
21
- args: ['--in-place']
22
- - repo: https://github.com/pycqa/isort
23
- rev: 5.12.0
24
- hooks:
25
- - id: isort
26
- - repo: https://github.com/pre-commit/mirrors-mypy
27
- rev: v0.991
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- hooks:
29
- - id: mypy
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- args: ['--ignore-missing-imports']
31
- - repo: https://github.com/google/yapf
32
- rev: v0.32.0
33
- hooks:
34
- - id: yapf
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- args: ['--parallel', '--in-place']
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  repos:
2
+ - repo: https://github.com/pre-commit/pre-commit-hooks
3
+ rev: v4.6.0
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+ hooks:
5
+ - id: check-executables-have-shebangs
6
+ - id: check-json
7
+ - id: check-merge-conflict
8
+ - id: check-shebang-scripts-are-executable
9
+ - id: check-toml
10
+ - id: check-yaml
11
+ - id: end-of-file-fixer
12
+ - id: mixed-line-ending
13
+ args: ["--fix=lf"]
14
+ - id: requirements-txt-fixer
15
+ - id: trailing-whitespace
16
+ - repo: https://github.com/myint/docformatter
17
+ rev: v1.7.5
18
+ hooks:
19
+ - id: docformatter
20
+ args: ["--in-place"]
21
+ - repo: https://github.com/pycqa/isort
22
+ rev: 5.13.2
23
+ hooks:
24
+ - id: isort
25
+ args: ["--profile", "black"]
26
+ - repo: https://github.com/pre-commit/mirrors-mypy
27
+ rev: v1.10.0
28
+ hooks:
29
+ - id: mypy
30
+ args: ["--ignore-missing-imports"]
31
+ additional_dependencies:
32
+ [
33
+ "types-python-slugify",
34
+ "types-requests",
35
+ "types-PyYAML",
36
+ "types-pytz",
37
+ ]
38
+ - repo: https://github.com/psf/black
39
+ rev: 24.4.2
40
+ hooks:
41
+ - id: black
42
+ language_version: python3.10
43
+ args: ["--line-length", "119"]
44
+ - repo: https://github.com/kynan/nbstripout
45
+ rev: 0.7.1
46
+ hooks:
47
+ - id: nbstripout
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+ args:
49
+ [
50
+ "--extra-keys",
51
+ "metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
52
+ ]
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+ - repo: https://github.com/nbQA-dev/nbQA
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+ rev: 1.8.5
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+ hooks:
56
+ - id: nbqa-black
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+ - id: nbqa-pyupgrade
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+ args: ["--py37-plus"]
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+ - id: nbqa-isort
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+ args: ["--float-to-top"]
.style.yapf DELETED
@@ -1,5 +0,0 @@
1
- [style]
2
- based_on_style = pep8
3
- blank_line_before_nested_class_or_def = false
4
- spaces_before_comment = 2
5
- split_before_logical_operator = true
 
 
 
 
 
 
.vscode/settings.json ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "editor.formatOnSave": true,
3
+ "files.insertFinalNewline": false,
4
+ "[python]": {
5
+ "editor.defaultFormatter": "ms-python.black-formatter",
6
+ "editor.formatOnType": true,
7
+ "editor.codeActionsOnSave": {
8
+ "source.organizeImports": "explicit"
9
+ }
10
+ },
11
+ "[jupyter]": {
12
+ "files.insertFinalNewline": false
13
+ },
14
+ "black-formatter.args": [
15
+ "--line-length=119"
16
+ ],
17
+ "isort.args": ["--profile", "black"],
18
+ "flake8.args": [
19
+ "--max-line-length=119"
20
+ ],
21
+ "ruff.lint.args": [
22
+ "--line-length=119"
23
+ ],
24
+ "notebook.output.scrolling": true,
25
+ "notebook.formatOnCellExecution": true,
26
+ "notebook.formatOnSave.enabled": true,
27
+ "notebook.codeActionsOnSave": {
28
+ "source.organizeImports": "explicit"
29
+ }
30
+ }
README.md CHANGED
@@ -4,7 +4,7 @@ emoji: 😻
4
  colorFrom: blue
5
  colorTo: yellow
6
  sdk: gradio
7
- sdk_version: 3.36.1
8
  app_file: app.py
9
  pinned: false
10
  ---
 
4
  colorFrom: blue
5
  colorTo: yellow
6
  sdk: gradio
7
+ sdk_version: 4.33.0
8
  app_file: app.py
9
  pinned: false
10
  ---
app.py CHANGED
@@ -2,7 +2,6 @@
2
 
3
  from __future__ import annotations
4
 
5
- import functools
6
  import pathlib
7
 
8
  import cv2
@@ -12,22 +11,19 @@ import insightface
12
  import numpy as np
13
  import onnxruntime as ort
14
 
15
- TITLE = 'insightface Person Detection'
16
- DESCRIPTION = 'https://github.com/deepinsight/insightface/tree/master/examples/person_detection'
17
 
18
 
19
  def load_model():
20
- path = huggingface_hub.hf_hub_download('public-data/insightface',
21
- 'models/scrfd_person_2.5g.onnx')
22
  options = ort.SessionOptions()
23
  options.intra_op_num_threads = 8
24
  options.inter_op_num_threads = 8
25
  session = ort.InferenceSession(
26
- path,
27
- sess_options=options,
28
- providers=['CPUExecutionProvider', 'CUDAExecutionProvider'])
29
- model = insightface.model_zoo.retinaface.RetinaFace(model_file=path,
30
- session=session)
31
  return model
32
 
33
 
@@ -47,8 +43,7 @@ def detect_person(
47
  return bboxes, vbboxes
48
 
49
 
50
- def visualize(image: np.ndarray, bboxes: np.ndarray,
51
- vbboxes: np.ndarray) -> np.ndarray:
52
  res = image.copy()
53
  for i in range(bboxes.shape[0]):
54
  bbox = bboxes[i]
@@ -59,9 +54,7 @@ def visualize(image: np.ndarray, bboxes: np.ndarray,
59
  alpha = 0.8
60
  color = (255, 0, 0)
61
  for c in range(3):
62
- res[vy1:vy2, vx1:vx2,
63
- c] = res[vy1:vy2, vx1:vx2,
64
- c] * alpha + color[c] * (1.0 - alpha)
65
  cv2.circle(res, (vx1, vy1), 1, color, 2)
66
  cv2.circle(res, (vx1, vy2), 1, color, 2)
67
  cv2.circle(res, (vx2, vy1), 1, color, 2)
@@ -69,26 +62,28 @@ def visualize(image: np.ndarray, bboxes: np.ndarray,
69
  return res
70
 
71
 
72
- def detect(image: np.ndarray, detector) -> np.ndarray:
 
 
 
 
73
  image = image[:, :, ::-1] # RGB -> BGR
74
  bboxes, vbboxes = detect_person(image, detector)
75
  res = visualize(image, bboxes, vbboxes)
76
  return res[:, :, ::-1] # BGR -> RGB
77
 
78
 
79
- detector = load_model()
80
- detector.prepare(-1, nms_thresh=0.5, input_size=(640, 640))
81
- fn = functools.partial(detect, detector=detector)
82
 
83
- image_dir = pathlib.Path('images')
84
- examples = [[path.as_posix()] for path in sorted(image_dir.glob('*.jpg'))]
85
-
86
- gr.Interface(
87
- fn=fn,
88
- inputs=gr.Image(label='Input', type='numpy'),
89
- outputs=gr.Image(label='Output', height=600),
90
  examples=examples,
91
  examples_per_page=30,
92
  title=TITLE,
93
  description=DESCRIPTION,
94
- ).queue().launch()
 
 
 
 
2
 
3
  from __future__ import annotations
4
 
 
5
  import pathlib
6
 
7
  import cv2
 
11
  import numpy as np
12
  import onnxruntime as ort
13
 
14
+ TITLE = "insightface Person Detection"
15
+ DESCRIPTION = "https://github.com/deepinsight/insightface/tree/master/examples/person_detection"
16
 
17
 
18
  def load_model():
19
+ path = huggingface_hub.hf_hub_download("public-data/insightface", "models/scrfd_person_2.5g.onnx")
 
20
  options = ort.SessionOptions()
21
  options.intra_op_num_threads = 8
22
  options.inter_op_num_threads = 8
23
  session = ort.InferenceSession(
24
+ path, sess_options=options, providers=["CPUExecutionProvider", "CUDAExecutionProvider"]
25
+ )
26
+ model = insightface.model_zoo.retinaface.RetinaFace(model_file=path, session=session)
 
 
27
  return model
28
 
29
 
 
43
  return bboxes, vbboxes
44
 
45
 
46
+ def visualize(image: np.ndarray, bboxes: np.ndarray, vbboxes: np.ndarray) -> np.ndarray:
 
47
  res = image.copy()
48
  for i in range(bboxes.shape[0]):
49
  bbox = bboxes[i]
 
54
  alpha = 0.8
55
  color = (255, 0, 0)
56
  for c in range(3):
57
+ res[vy1:vy2, vx1:vx2, c] = res[vy1:vy2, vx1:vx2, c] * alpha + color[c] * (1.0 - alpha)
 
 
58
  cv2.circle(res, (vx1, vy1), 1, color, 2)
59
  cv2.circle(res, (vx1, vy2), 1, color, 2)
60
  cv2.circle(res, (vx2, vy1), 1, color, 2)
 
62
  return res
63
 
64
 
65
+ detector = load_model()
66
+ detector.prepare(-1, nms_thresh=0.5, input_size=(640, 640))
67
+
68
+
69
+ def detect(image: np.ndarray) -> np.ndarray:
70
  image = image[:, :, ::-1] # RGB -> BGR
71
  bboxes, vbboxes = detect_person(image, detector)
72
  res = visualize(image, bboxes, vbboxes)
73
  return res[:, :, ::-1] # BGR -> RGB
74
 
75
 
76
+ examples = sorted(pathlib.Path("images").glob("*.jpg"))
 
 
77
 
78
+ demo = gr.Interface(
79
+ fn=detect,
80
+ inputs=gr.Image(label="Input", type="numpy"),
81
+ outputs=gr.Image(label="Output"),
 
 
 
82
  examples=examples,
83
  examples_per_page=30,
84
  title=TITLE,
85
  description=DESCRIPTION,
86
+ )
87
+
88
+ if __name__ == "__main__":
89
+ demo.queue(max_size=10).launch()
pre-requirements.txt CHANGED
@@ -1 +1 @@
1
- Cython==0.29.36
 
1
+ Cython==3.0.10
requirements.txt CHANGED
@@ -1,3 +1,3 @@
1
  insightface==0.7.3
2
- onnxruntime==1.15.1
3
- opencv-python-headless==4.8.0.74
 
1
  insightface==0.7.3
2
+ onnxruntime==1.18.0
3
+ opencv-python-headless==4.10.0.82