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continue lintings on readme
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README.md
26
README.md
@ -65,7 +65,7 @@ This function verifies face pairs as same person or different persons. It expect
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```python
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```python
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result = DeepFace.verify(
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result = DeepFace.verify(
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img1_path = "img1.jpg",
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img1_path = "img1.jpg",
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img2_path = "img2.jpg"
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img2_path = "img2.jpg",
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)
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)
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```
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```
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@ -79,7 +79,7 @@ result = DeepFace.verify(
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```python
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```python
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dfs = DeepFace.find(
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dfs = DeepFace.find(
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img_path = "img1.jpg",
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img_path = "img1.jpg",
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db_path = "C:/workspace/my_db"
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db_path = "C:/workspace/my_db",
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)
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)
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```
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```
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@ -133,20 +133,20 @@ models = [
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result = DeepFace.verify(
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result = DeepFace.verify(
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img1_path = "img1.jpg",
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img1_path = "img1.jpg",
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img2_path = "img2.jpg",
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img2_path = "img2.jpg",
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model_name = models[0]
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model_name = models[0],
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)
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)
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#face recognition
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#face recognition
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dfs = DeepFace.find(
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dfs = DeepFace.find(
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img_path = "img1.jpg",
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img_path = "img1.jpg",
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db_path = "C:/workspace/my_db",
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db_path = "C:/workspace/my_db",
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model_name = models[1]
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model_name = models[1],
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)
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)
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#embeddings
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#embeddings
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embedding_objs = DeepFace.represent(
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embedding_objs = DeepFace.represent(
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img_path = "img.jpg",
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img_path = "img.jpg",
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model_name = models[2]
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model_name = models[2],
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)
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)
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```
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```
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@ -183,14 +183,14 @@ metrics = ["cosine", "euclidean", "euclidean_l2"]
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result = DeepFace.verify(
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result = DeepFace.verify(
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img1_path = "img1.jpg",
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img1_path = "img1.jpg",
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img2_path = "img2.jpg",
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img2_path = "img2.jpg",
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distance_metric = metrics[1]
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distance_metric = metrics[1],
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)
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)
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#face recognition
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#face recognition
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dfs = DeepFace.find(
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dfs = DeepFace.find(
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img_path = "img1.jpg",
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img_path = "img1.jpg",
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db_path = "C:/workspace/my_db",
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db_path = "C:/workspace/my_db",
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distance_metric = metrics[2]
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distance_metric = metrics[2],
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)
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)
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```
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```
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@ -203,7 +203,7 @@ Deepface also comes with a strong facial attribute analysis module including [`a
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```python
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```python
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objs = DeepFace.analyze(
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objs = DeepFace.analyze(
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img_path = "img4.jpg",
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img_path = "img4.jpg",
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actions = ['age', 'gender', 'race', 'emotion']
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actions = ['age', 'gender', 'race', 'emotion'],
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)
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)
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```
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```
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@ -238,32 +238,32 @@ backends = [
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obj = DeepFace.verify(
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obj = DeepFace.verify(
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img1_path = "img1.jpg",
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img1_path = "img1.jpg",
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img2_path = "img2.jpg",
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img2_path = "img2.jpg",
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detector_backend = backends[0]
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detector_backend = backends[0],
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)
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)
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#face recognition
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#face recognition
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dfs = DeepFace.find(
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dfs = DeepFace.find(
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img_path = "img.jpg",
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img_path = "img.jpg",
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db_path = "my_db",
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db_path = "my_db",
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detector_backend = backends[1]
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detector_backend = backends[1],
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)
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)
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#embeddings
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#embeddings
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embedding_objs = DeepFace.represent(
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embedding_objs = DeepFace.represent(
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img_path = "img.jpg",
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img_path = "img.jpg",
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detector_backend = backends[2]
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detector_backend = backends[2],
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)
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)
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#facial analysis
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#facial analysis
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demographies = DeepFace.analyze(
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demographies = DeepFace.analyze(
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img_path = "img4.jpg",
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img_path = "img4.jpg",
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detector_backend = backends[3]
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detector_backend = backends[3],
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)
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)
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#face detection and alignment
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#face detection and alignment
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face_objs = DeepFace.extract_faces(
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face_objs = DeepFace.extract_faces(
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img_path = "img.jpg",
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img_path = "img.jpg",
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detector_backend = backends[4]
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detector_backend = backends[4],
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)
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)
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```
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```
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