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74 lines
2.2 KiB
Python
74 lines
2.2 KiB
Python
import cv2
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import pandas as pd
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from deepface import DeepFace
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from deepface.commons import distance
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from deepface.commons.logger import Logger
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logger = Logger("tests/test_find.py")
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threshold = distance.findThreshold(model_name="VGG-Face", distance_metric="cosine")
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def test_find_with_exact_path():
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img_path = "dataset/img1.jpg"
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dfs = DeepFace.find(img_path=img_path, db_path="dataset", silent=True)
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assert len(dfs) > 0
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for df in dfs:
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assert isinstance(df, pd.DataFrame)
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# one is img1.jpg itself
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identity_df = df[df["identity"] == img_path]
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assert identity_df.shape[0] > 0
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# validate reproducability
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assert identity_df["distance"].values[0] < threshold
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df = df[df["identity"] != img_path]
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logger.debug(df.head())
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assert df.shape[0] > 0
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logger.info("✅ test find for exact path done")
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def test_find_with_array_input():
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img_path = "dataset/img1.jpg"
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img1 = cv2.imread(img_path)
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dfs = DeepFace.find(img1, db_path="dataset", silent=True)
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assert len(dfs) > 0
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for df in dfs:
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assert isinstance(df, pd.DataFrame)
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# one is img1.jpg itself
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identity_df = df[df["identity"] == img_path]
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assert identity_df.shape[0] > 0
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# validate reproducability
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assert identity_df["distance"].values[0] < threshold
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df = df[df["identity"] != img_path]
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logger.debug(df.head())
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assert df.shape[0] > 0
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logger.info("✅ test find for array input done")
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def test_find_with_extracted_faces():
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img_path = "dataset/img1.jpg"
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face_objs = DeepFace.extract_faces(img_path)
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img = face_objs[0]["face"]
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dfs = DeepFace.find(img, db_path="dataset", detector_backend="skip", silent=True)
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assert len(dfs) > 0
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for df in dfs:
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assert isinstance(df, pd.DataFrame)
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# one is img1.jpg itself
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identity_df = df[df["identity"] == img_path]
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assert identity_df.shape[0] > 0
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# validate reproducability
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assert identity_df["distance"].values[0] < threshold
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df = df[df["identity"] != img_path]
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logger.debug(df.head())
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assert df.shape[0] > 0
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logger.info("✅ test find for extracted face input done")
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