continue lintings on readme

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Sefik Ilkin Serengil 2024-05-05 07:55:14 +01:00 committed by GitHub
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@ -65,7 +65,7 @@ This function verifies face pairs as same person or different persons. It expect
```python ```python
result = DeepFace.verify( result = DeepFace.verify(
img1_path = "img1.jpg", img1_path = "img1.jpg",
img2_path = "img2.jpg" img2_path = "img2.jpg",
) )
``` ```
@ -79,7 +79,7 @@ result = DeepFace.verify(
```python ```python
dfs = DeepFace.find( dfs = DeepFace.find(
img_path = "img1.jpg", img_path = "img1.jpg",
db_path = "C:/workspace/my_db" db_path = "C:/workspace/my_db",
) )
``` ```
@ -133,20 +133,20 @@ models = [
result = DeepFace.verify( result = DeepFace.verify(
img1_path = "img1.jpg", img1_path = "img1.jpg",
img2_path = "img2.jpg", img2_path = "img2.jpg",
model_name = models[0] model_name = models[0],
) )
#face recognition #face recognition
dfs = DeepFace.find( dfs = DeepFace.find(
img_path = "img1.jpg", img_path = "img1.jpg",
db_path = "C:/workspace/my_db", db_path = "C:/workspace/my_db",
model_name = models[1] model_name = models[1],
) )
#embeddings #embeddings
embedding_objs = DeepFace.represent( embedding_objs = DeepFace.represent(
img_path = "img.jpg", img_path = "img.jpg",
model_name = models[2] model_name = models[2],
) )
``` ```
@ -183,14 +183,14 @@ metrics = ["cosine", "euclidean", "euclidean_l2"]
result = DeepFace.verify( result = DeepFace.verify(
img1_path = "img1.jpg", img1_path = "img1.jpg",
img2_path = "img2.jpg", img2_path = "img2.jpg",
distance_metric = metrics[1] distance_metric = metrics[1],
) )
#face recognition #face recognition
dfs = DeepFace.find( dfs = DeepFace.find(
img_path = "img1.jpg", img_path = "img1.jpg",
db_path = "C:/workspace/my_db", db_path = "C:/workspace/my_db",
distance_metric = metrics[2] distance_metric = metrics[2],
) )
``` ```
@ -203,7 +203,7 @@ Deepface also comes with a strong facial attribute analysis module including [`a
```python ```python
objs = DeepFace.analyze( objs = DeepFace.analyze(
img_path = "img4.jpg", img_path = "img4.jpg",
actions = ['age', 'gender', 'race', 'emotion'] actions = ['age', 'gender', 'race', 'emotion'],
) )
``` ```
@ -238,32 +238,32 @@ backends = [
obj = DeepFace.verify( obj = DeepFace.verify(
img1_path = "img1.jpg", img1_path = "img1.jpg",
img2_path = "img2.jpg", img2_path = "img2.jpg",
detector_backend = backends[0] detector_backend = backends[0],
) )
#face recognition #face recognition
dfs = DeepFace.find( dfs = DeepFace.find(
img_path = "img.jpg", img_path = "img.jpg",
db_path = "my_db", db_path = "my_db",
detector_backend = backends[1] detector_backend = backends[1],
) )
#embeddings #embeddings
embedding_objs = DeepFace.represent( embedding_objs = DeepFace.represent(
img_path = "img.jpg", img_path = "img.jpg",
detector_backend = backends[2] detector_backend = backends[2],
) )
#facial analysis #facial analysis
demographies = DeepFace.analyze( demographies = DeepFace.analyze(
img_path = "img4.jpg", img_path = "img4.jpg",
detector_backend = backends[3] detector_backend = backends[3],
) )
#face detection and alignment #face detection and alignment
face_objs = DeepFace.extract_faces( face_objs = DeepFace.extract_faces(
img_path = "img.jpg", img_path = "img.jpg",
detector_backend = backends[4] detector_backend = backends[4],
) )
``` ```