| |
| import os |
| from PIL import Image |
| import pandas as pd |
| from transformers import pipeline |
|
|
| |
| |
| age_classifier = pipeline("image-classification", model="nateraw/vit-age-classifier") |
| |
| gender_classifier = pipeline("image-classification", model="rizvandwiki/gender-classification") |
| |
| emotion_classifier = pipeline("image-classification", model="Rajaram1996/Happiness-Classifier") |
|
|
| |
| image_folder = "images/" |
| image_files = [f for f in os.listdir(image_folder) if f.endswith(('.jpg', '.png'))] |
|
|
| |
| results = [] |
|
|
| |
| for image_file in image_files: |
| image_path = os.path.join(image_folder, image_file) |
| image = Image.open(image_path) |
|
|
| |
| age_prediction = age_classifier(image) |
| predicted_age = age_prediction[0]['label'] |
|
|
| |
| gender_prediction = gender_classifier(image) |
| predicted_gender = gender_prediction[0]['label'] |
|
|
| |
| emotion_prediction = emotion_classifier(image) |
| predicted_happiness = emotion_prediction[0]['label'] |
|
|
| |
| results.append({ |
| "Image Name": image_file, |
| "Predicted Age": predicted_age, |
| "Predicted Gender": predicted_gender, |
| "Predicted Happiness": predicted_happiness |
| }) |
|
|
| |
| df = pd.DataFrame(results) |
| df.to_csv("participant_classification_report.csv", index=False) |
|
|
| print("分类完成，结果已保存到 participant_classification_report.csv") |
|
|
