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  1. README.md +5 -0
  2. app.py +1 -1
  3. pyproject.toml +15 -2
  4. src/faceverification/core/image_processor.py +5 -7
  5. src/faceverification/core/vectordb.py +3 -3
  6. src/faceverification/{app.py → interfaces/gradio_app.py} +2 -6
  7. uv.lock +205 -0
README.md CHANGED
@@ -8,14 +8,19 @@ sdk_version: 6.14.0
8
  python_version: '3.11'
9
  app_file: app.py
10
  short_description: "Face verification demo with FaceNet and VectorDB"
 
11
  pinned: false
12
  license: mit
13
  ---
 
 
14
 
15
  # Face Verification
16
 
17
  AI Engineering Demo project demonstrating an end-to-end face verification workflow with FaceNet embeddings, ChromaDB vector search, and an interactive Gradio interface.
18
 
 
 
19
  The app lets users add known people to a local embeddings database and verify whether a new face image matches one of the stored identities.
20
 
21
  ## Features
 
8
  python_version: '3.11'
9
  app_file: app.py
10
  short_description: "Face verification demo with FaceNet and VectorDB"
11
+ tags: ["face-verification", "computer-vision", "facenet", "vector-database"]
12
  pinned: false
13
  license: mit
14
  ---
15
+ ![CI](https://github.com/leandrodevai/faceverification/actions/workflows/ci.yml/badge.svg)
16
+ ![Deploy](https://github.com/leandrodevai/faceverification/actions/workflows/deploy-to-HSspaces.yml/badge.svg)
17
 
18
  # Face Verification
19
 
20
  AI Engineering Demo project demonstrating an end-to-end face verification workflow with FaceNet embeddings, ChromaDB vector search, and an interactive Gradio interface.
21
 
22
+ Try it on Hugging Face Spaces: https://huggingface.co/spaces/leandrodevai/faceverification
23
+
24
  The app lets users add known people to a local embeddings database and verify whether a new face image matches one of the stored identities.
25
 
26
  ## Features
app.py CHANGED
@@ -3,7 +3,7 @@ from pathlib import Path
3
 
4
  sys.path.insert(0, str(Path(__file__).parent / "src"))
5
 
6
- from faceverification.app import FV_gr
7
 
8
  if __name__ == "__main__":
9
  FV_gr.launch()
 
3
 
4
  sys.path.insert(0, str(Path(__file__).parent / "src"))
5
 
6
+ from faceverification.interfaces.gradio_app import FV_gr
7
 
8
  if __name__ == "__main__":
9
  FV_gr.launch()
pyproject.toml CHANGED
@@ -1,7 +1,7 @@
1
  [project]
2
  name = "faceverification"
3
  version = "0.1.0"
4
- description = "Add your description here"
5
  readme = "README.md"
6
  requires-python = ">=3.11"
7
  dependencies = [
@@ -16,10 +16,14 @@ dependencies = [
16
  "torchvision>=0.26.0",
17
  "chromadb>=1.5.9",
18
  "pytest>=9.0.3",
 
 
 
 
19
  ]
20
 
21
  [project.scripts]
22
- faceverification = "faceverification.app:main"
23
 
24
  [build-system]
25
  requires = ["setuptools>=68"]
@@ -45,3 +49,12 @@ markers = [
45
  "integration: tests that use real external components or models",
46
  "e2e: end-to-end tests that exercise complete application workflows",
47
  ]
 
 
 
 
 
 
 
 
 
 
1
  [project]
2
  name = "faceverification"
3
  version = "0.1.0"
4
+ description = "Face verification demo using FaceNet embeddings, ChromaDB vector search, and CI/CD pipeline."
5
  readme = "README.md"
6
  requires-python = ">=3.11"
7
  dependencies = [
 
16
  "torchvision>=0.26.0",
17
  "chromadb>=1.5.9",
18
  "pytest>=9.0.3",
19
+ "pytest-cov>=7.1.0",
20
+ "fastapi>=0.136.1",
21
+ "uvicorn[standard]>=0.46.0",
22
+ "ruff>=0.15.13",
23
  ]
24
 
25
  [project.scripts]
26
+ faceverification = "faceverification.interfaces.gradio_app:main"
27
 
28
  [build-system]
29
  requires = ["setuptools>=68"]
 
49
  "integration: tests that use real external components or models",
50
  "e2e: end-to-end tests that exercise complete application workflows",
51
  ]
52
+
53
+ [tool.ruff]
54
+ line-length = 100
55
+ target-version = "py311"
56
+ src = ["src", "test"]
57
+
58
+ [tool.ruff.lint]
59
+ select = ["E", "F", "I", "B", "UP", "SIM"]
60
+
src/faceverification/core/image_processor.py CHANGED
@@ -62,9 +62,7 @@ class ImageProcessor:
62
  device=self.device,
63
  thresholds=list(mtcnn_thresholds),
64
  )
65
- self.facenet = (
66
- InceptionResnetV1(pretrained=facenet_pretrained).eval().to(self.device)
67
- )
68
 
69
  def get_embedding(self, image: Image.Image) -> torch.Tensor:
70
  """Return a normalized embedding for the detected face in an image.
@@ -82,9 +80,9 @@ class ImageProcessor:
82
  if face_tensor is None:
83
  raise FaceNotDetectedError("No face detected in the image.")
84
 
85
- face_tensor = (
86
- face_tensor.unsqueeze(0) if face_tensor.ndim == 3 else face_tensor
87
- ).to(self.device)
88
 
89
  with torch.no_grad():
90
  features = self.facenet(face_tensor)
@@ -108,7 +106,7 @@ class ImageProcessor:
108
  return image, False
109
 
110
  draw = ImageDraw.Draw(image)
111
- for box, prob in zip(boxes, probs):
112
  x1, y1, x2, y2 = [int(v) for v in box]
113
  draw.rectangle([x1, y1, x2, y2], outline="red", width=2)
114
  draw.text((x1, max(0, y1 - 12)), f"{prob:.4f}", fill="red")
 
62
  device=self.device,
63
  thresholds=list(mtcnn_thresholds),
64
  )
65
+ self.facenet = InceptionResnetV1(pretrained=facenet_pretrained).eval().to(self.device)
 
 
66
 
67
  def get_embedding(self, image: Image.Image) -> torch.Tensor:
68
  """Return a normalized embedding for the detected face in an image.
 
80
  if face_tensor is None:
81
  raise FaceNotDetectedError("No face detected in the image.")
82
 
83
+ face_tensor = (face_tensor.unsqueeze(0) if face_tensor.ndim == 3 else face_tensor).to(
84
+ self.device
85
+ )
86
 
87
  with torch.no_grad():
88
  features = self.facenet(face_tensor)
 
106
  return image, False
107
 
108
  draw = ImageDraw.Draw(image)
109
+ for box, prob in zip(boxes, probs, strict=True):
110
  x1, y1, x2, y2 = [int(v) for v in box]
111
  draw.rectangle([x1, y1, x2, y2], outline="red", width=2)
112
  draw.text((x1, max(0, y1 - 12)), f"{prob:.4f}", fill="red")
src/faceverification/core/vectordb.py CHANGED
@@ -7,7 +7,8 @@ filtering.
7
  """
8
 
9
  import uuid
10
- from typing import Any, Mapping
 
11
 
12
  import chromadb
13
  import numpy as np
@@ -105,8 +106,7 @@ class VectorDB:
105
  embeddings = result.get("embeddings")
106
  if not embeddings or embeddings[0] is None or len(embeddings[0]) == 0:
107
  raise ValueError(
108
- "No record found in the vector database. "
109
- "Add a person before verifying faces."
110
  )
111
 
112
  best_dist = 100000
 
7
  """
8
 
9
  import uuid
10
+ from collections.abc import Mapping
11
+ from typing import Any
12
 
13
  import chromadb
14
  import numpy as np
 
106
  embeddings = result.get("embeddings")
107
  if not embeddings or embeddings[0] is None or len(embeddings[0]) == 0:
108
  raise ValueError(
109
+ "No record found in the vector database. Add a person before verifying faces."
 
110
  )
111
 
112
  best_dist = 100000
src/faceverification/{app.py → interfaces/gradio_app.py} RENAMED
@@ -31,12 +31,8 @@ with gr.Blocks() as FV_gr:
31
  with gr.Tabs():
32
  with gr.TabItem("Add Person"):
33
  with gr.Row():
34
- input_image = gr.Image(
35
- label="Upload an image with a clear face", type="pil"
36
- )
37
- input_name = gr.Textbox(
38
- label="Person name", placeholder="Example: John Doe"
39
- )
40
  output_image = gr.Image(label="Detection result")
41
  submit_btn = gr.Button("Add to database")
42
  submit_btn.click(
 
31
  with gr.Tabs():
32
  with gr.TabItem("Add Person"):
33
  with gr.Row():
34
+ input_image = gr.Image(label="Upload an image with a clear face", type="pil")
35
+ input_name = gr.Textbox(label="Person name", placeholder="Example: John Doe")
 
 
 
 
36
  output_image = gr.Image(label="Detection result")
37
  submit_btn = gr.Button("Add to database")
38
  submit_btn.click(
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527
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529
  [[package]]
530
  name = "cuda-bindings"
531
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@@ -666,14 +770,18 @@ dependencies = [
666
  { name = "chromadb" },
667
  { name = "datasets" },
668
  { name = "facenet-pytorch" },
 
669
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670
  { name = "huggingface-hub" },
671
  { name = "numpy" },
672
  { name = "pydantic-settings" },
673
  { name = "pytest" },
 
674
  { name = "python-dotenv" },
 
675
  { name = "torch" },
676
  { name = "torchvision" },
 
677
  ]
678
 
679
  [package.metadata]
@@ -681,14 +789,18 @@ requires-dist = [
681
  { name = "chromadb", specifier = ">=1.5.9" },
682
  { name = "datasets", specifier = ">=4.8.5" },
683
  { name = "facenet-pytorch", specifier = ">=2.5.3" },
 
684
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685
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686
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687
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688
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689
  { name = "python-dotenv", specifier = ">=1.2.2" },
 
690
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691
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692
  ]
693
 
694
  [[package]]
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2686
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2687
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2688
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2689
  [[package]]
2690
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2691
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@@ -2943,6 +3069,31 @@ wheels = [
2943
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2944
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2945
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2946
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2947
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2948
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3052
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3053
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3055
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3056
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3057
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529
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770
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771
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772
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783
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784
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787
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789
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790
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806
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2798
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2801
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2803
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2804
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2816
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2817
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3069
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3070
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3072
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3261
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3262
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