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| import streamlit as st | |
| from transformers import pipeline | |
| from PIL import Image | |
| MODEL_1 = "google/vit-base-patch16-224" | |
| MIN_ACEPTABLE_SCORE = 0.1 | |
| MAX_N_LABELS = 5 | |
| MODEL_2 = "nateraw/vit-age-classifier" | |
| MODELS = [ | |
| "google/vit-base-patch16-224", #Classifição geral | |
| "nateraw/vit-age-classifier", #Classifição de idade | |
| "microsoft/resnet-50", #Classifição geral | |
| "Falconsai/nsfw_image_detection", #Classifição NSFW | |
| "cafeai/cafe_aesthetic", #Classifição de estética | |
| "microsoft/resnet-18", #Classifição geral | |
| "microsoft/resnet-34", #Classifição geral escolhida pelo copilot | |
| "microsoft/resnet-101", #Classifição geral escolhida pelo copilot | |
| "microsoft/resnet-152", #Classifição geral escolhida pelo copilot | |
| "microsoft/swin-tiny-patch4-window7-224",#Classifição geral | |
| "-- Reinstated on testing--", | |
| "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral | |
| "-- New --" | |
| "-- Still in the testing process --" | |
| "facebook/convnext-large-224" | |
| "timm/resnet50.a1_in1k" | |
| "timm/mobilenetv3_large_100.ra_in1k" | |
| "trpakov/vit-face-expression" | |
| "rizvandwiki/gender-classification" | |
| "#q-future/one-align" | |
| "LukeJacob2023/nsfw-image-detector" | |
| "vit-base-patch16-224-in21k" | |
| "not-lain/deepfake" | |
| "carbon225/vit-base-patch16-224-hentai" | |
| "facebook/convnext-base-224-22k-1k" | |
| "facebook/convnext-large-224" | |
| "facebook/convnext-tiny-224" | |
| "nvidia/mit-b0" | |
| "microsoft/resnet-18" | |
| "microsoft/swinv2-base-patch4-window16-256" | |
| "andupets/real-estate-image-classification" | |
| "timm/tf_efficientnetv2_s.in21k" | |
| "timm/convnext_tiny.fb_in22k" | |
| "DunnBC22/vit-base-patch16-224-in21k_Human_Activity_Recognition" | |
| "FatihC/swin-tiny-patch4-window7-224-finetuned-eurosat-watermark" | |
| "aalonso-developer/vit-base-patch16-224-in21k-clothing-classifier" | |
| "RickyIG/emotion_face_image_classification" | |
| "shadowlilac/aesthetic-shadow" | |
| ] | |
| def classify(image, model): | |
| classifier = pipeline("image-classification", model=model) | |
| result= classifier(image) | |
| return result | |
| def save_result(result): | |
| st.write("In the future, this function will save the result in a database.") | |
| def print_result(result): | |
| comulative_discarded_score = 0 | |
| for i in range(len(result)): | |
| if result[i]['score'] < MIN_ACEPTABLE_SCORE: | |
| comulative_discarded_score += result[i]['score'] | |
| else: | |
| st.write(result[i]['label']) | |
| st.progress(result[i]['score']) | |
| st.write(result[i]['score']) | |
| st.write(f"comulative_discarded_score:") | |
| st.progress(comulative_discarded_score) | |
| st.write(comulative_discarded_score) | |
| def main(): | |
| st.title("Image Classification") | |
| st.write("This is a simple web app to test and compare different image classifier models using Hugging Face's image-classification pipeline.") | |
| st.write("From time to time more models will be added to the list. If you want to add a model, please open an issue on the GitHub repository.") | |
| st.markdown("[](http://google.com.au/)") | |
| input_image = st.file_uploader("Upload Image") | |
| shosen_model = st.selectbox("Select the model to use", MODELS) | |
| if input_image is not None: | |
| image_to_classify = Image.open(input_image) | |
| st.image(image_to_classify, caption="Uploaded Image", use_column_width=True) | |
| if st.button("Classify"): | |
| image_to_classify = Image.open(input_image) | |
| classification_obj1 =[] | |
| avable_models = st.selectbox | |
| classification_result = classify(image_to_classify, shosen_model) | |
| classification_obj1.append(classification_result) | |
| print_result(classification_result) | |
| save_result(classification_result) | |
| if __name__ == "__main__": | |
| main() |