70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
# -*- coding: utf-8 -*-
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"""Untitled0.ipynb
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Automatically generated by Colaboratory.
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Original file is located at
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https://colab.research.google.com/drive/15cy6ue9c3bBkppUv3w09d9JJNebdeBuV
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"""
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# Install deepface framework.
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!pip install deepface
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# Install matplotlib
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!pip install matplotlib
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!pip install dlib
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# Load deepface libary
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from deepface import DeepFace
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# Import OpenCV to read images
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import cv2
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# Import matplotlib to plot images
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import matplotlib.pyplot as plt
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import pandas as pd
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def verify(img1_path, img2_path):
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# read images
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img1 = cv2.imread('images/' + img1_path)
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img2 = cv2.imread('images/' + img2_path)
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# plot images
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img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2RGB)
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plt.imshow(img1)
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plt.show()
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img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2RGB)
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plt.imshow(img2)
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plt.show()
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# Loop models and print results
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models = ["DeepFace", "Facenet", "VGG-Face", "Dlib"]
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for model in models:
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result = DeepFace.verify('images/' + img1_path, 'images/' + img2_path, model_name = model)
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print (model + ' result: ', result)
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verify("angelinajolie2.jpg", "angelinajolie4.jpg")
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verify("jenniferaniston.jpg", "reesewitherspoon.jpg")
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def find(img_path):
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# read images
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img = cv2.imread(img_path)
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# plot images
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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plt.imshow(img)
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plt.show()
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# Loop models and print results
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models = ["DeepFace", "Facenet", "VGG-Face"]
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for model in models:
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result = DeepFace.find(img_path, db_path = "images", model_name = model, distance_metric = 'cosine')
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print (model + ' result: ', result)
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# plot all verified images
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for result_table in result.iloc:
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print("File: " + result_table.identity)
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# plot image
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img = cv2.imread(result_table.identity)
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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plt.imshow(img)
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plt.show()
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find("dicaprio.jpg") |