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Runtime error
| from statistics import mode | |
| import streamlit as st | |
| from fastai.vision.all import * | |
| from PIL import Image | |
| from Processor import Processor | |
| def initialize_app(): | |
| return Processor(load_learner('model.pkl')) | |
| def process_images(images, processor: Processor): | |
| filtered_images = [] | |
| result = [] | |
| class_names = list( | |
| map(lambda name: {name: 0}, processor.inference.dls.vocab)) | |
| for image in images: | |
| image = Image.open(image) | |
| if processor.filter_image(image): | |
| filtered_images.append(np.asarray(image)) | |
| for img in filtered_images: | |
| result.append(processor.classify_image(img)[0]) | |
| if len(result) == 0: | |
| return None | |
| for res_name in result: | |
| for idx, class_name in enumerate(class_names): | |
| for key, value in class_name.items(): | |
| if res_name == key: | |
| class_names[idx][key] = value + 1 | |
| outfit = mode(result) | |
| with open(f'./texts/{outfit}.txt') as text: | |
| personality = text.read() | |
| return {'outfit': outfit.title(), 'personality': personality, | |
| 'chart': class_names} | |
| # Streamlit UI | |
| processor = initialize_app() | |
| st.title('Instagram Clothes Psychology (Photos)') | |
| uploaded_photos = st.file_uploader(label="Upload photos", type=[ | |
| 'jpg', 'jpeg'], accept_multiple_files=True) | |
| photos_empty = True if len(uploaded_photos) == 0 else False | |
| is_clicked = st.button(label='Predict Personality', | |
| disabled=photos_empty) | |
| if is_clicked: | |
| with st.spinner('Please wait...'): | |
| result = process_images(uploaded_photos, processor) | |
| if result is None: | |
| st.write('Tidak ditemukan gambar yang valid') | |
| else: | |
| st.header('Your personality is..') | |
| st.subheader(result['outfit']) | |
| st.markdown(result['personality']) | |
| st.bar_chart(result['chart']) | |