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| from deepface import DeepFace | |
| import pandas as pd | |
| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| import tempfile | |
| import os | |
| def faceAnalyzer(image_path): | |
| def analyze(image_path, attribute): | |
| analysis = DeepFace.analyze(img_path=image_path, actions=['gender', 'race', 'emotion', 'age']) | |
| df = pd.DataFrame(analysis[0]) | |
| plot = df[attribute].plot(kind='line', figsize=(9, 5), title=attribute).get_figure() | |
| _, temp_filename = tempfile.mkstemp(suffix=".png") | |
| plot.savefig(temp_filename, dpi=600) | |
| plt.close(plot) | |
| return temp_filename | |
| attributes = ['gender', 'race', 'emotion'] | |
| images = [analyze(image_path, attribute) for attribute in attributes] | |
| return [gr.Image(image) for attribute, image in zip(attributes, images)] | |
| def faceAnalyzer2(image_path, attribute): | |
| analysis = DeepFace.analyze(img_path=image_path, actions=['age', 'gender', 'race', 'emotion']) | |
| # convert the resulting dictionary to a DataFrame | |
| df = pd.DataFrame(analysis[0]) | |
| if attribute == "gender": | |
| gender = df['gender'].plot(kind = 'line', figsize = (9, 5), title = 'Gender').get_figure() | |
| return gender | |
| elif attribute == "race": | |
| race = df['race'].plot(kind = 'line', figsize = (9, 5), title = 'Race').get_figure() | |
| return race | |
| elif attribute == "emotion": | |
| emotion = df['emotion'].plot(kind = 'line', figsize = (9, 5), title = 'Emotion').get_figure() | |
| return emotion | |
| app1 = gr.Interface(faceAnalyzer, | |
| inputs=gr.Image(label="Upload Photo"), | |
| outputs=[gr.Image(label="Gender Analysis"), | |
| gr.Image(label="Race Analysis"), | |
| gr.Image(label="Emotion Analysis")], | |
| theme=gr.themes.Soft()) | |
| app2 = gr.Interface(faceAnalyzer2, | |
| inputs=[gr.Image(label="Upload Photo"),gr.Radio(choices=["gender","race","emotion"], | |
| value="gender", | |
| label="Attributes", | |
| info="Select an attribute")], | |
| outputs=gr.Plot(label="Analysis Output"), | |
| theme=gr.themes.Soft()) | |
| application = gr.TabbedInterface([app1,app2],["Full Analysis","Select Analysis"],theme=gr.themes.Soft()) | |
| application.launch() | |