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| import streamlit as st | |
| import pandas as pd | |
| from PIL import Image, ImageDraw, ImageFont | |
| import io | |
| def main(): | |
| # Sidebar logo and title | |
| with st.sidebar: | |
| col1, col2 = st.columns([1, 5]) # Shrink the logo column and expand the text column | |
| with col1: | |
| logo = Image.open("logo.png") | |
| resized_logo = logo.resize((40, 40)) # Resize the logo | |
| st.image(resized_logo) | |
| with col2: | |
| st.markdown( | |
| """ | |
| <div style=" | |
| display: flex; | |
| align-items: center; | |
| gap: 10px; | |
| margin: 0; | |
| padding: 0; | |
| font-family: 'Inter', sans-serif; | |
| font-size: 26px; | |
| font-weight: bold;"> | |
| AI Energy Score | |
| </div> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| # Sidebar instructions and link | |
| st.sidebar.markdown( | |
| """ | |
| <h1 style="text-align: center; font-size: 24px; font-weight: bold;"> | |
| Generate a Label to Display your | |
| <a href="https://huggingface.co/spaces/AIEnergyScore/Leaderboard" target="_blank" style="text-decoration: none; color: inherit;"> | |
| AI Energy Score | |
| </a> | |
| </h1> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.sidebar.markdown("<hr style='border: 1px solid gray; margin: 15px 0;'>", unsafe_allow_html=True) | |
| # Load CSV | |
| try: | |
| data_df = pd.read_csv("data.csv") | |
| except FileNotFoundError: | |
| st.sidebar.error("Could not find 'data.csv'! Please make sure it's present.") | |
| return | |
| except Exception as e: | |
| st.sidebar.error(f"Error reading 'data.csv': {e}") | |
| return | |
| # Check columns | |
| required_columns = ["model", "provider", "date", "task", "hardware", "energy", "score"] | |
| for col in required_columns: | |
| if col not in data_df.columns: | |
| st.sidebar.error(f"The CSV file must contain a column named '{col}'.") | |
| return | |
| st.sidebar.write("### Instructions:") | |
| st.sidebar.write("#### 1. Select a model below") | |
| model_options = data_df["model"].unique().tolist() | |
| selected_model = st.sidebar.selectbox( | |
| "Scored Models", | |
| model_options, | |
| help="Start typing to search for a model" | |
| ) | |
| st.sidebar.write("#### 2. Download the label") | |
| model_data = data_df[data_df["model"] == selected_model].iloc[0] | |
| # Select background by score | |
| try: | |
| score = int(model_data["score"]) | |
| background_path = f"{score}.png" | |
| background = Image.open(background_path).convert("RGBA") | |
| except FileNotFoundError: | |
| st.sidebar.error(f"Could not find background image '{score}.png'. Using default background.") | |
| background = Image.open("default_background.png").convert("RGBA") | |
| except ValueError: | |
| st.sidebar.error(f"Invalid score '{model_data['score']}'. Score must be an integer.") | |
| return | |
| # Keep the final label size at 520×728 | |
| final_size = (520, 728) | |
| generated_label = create_label_single_pass(background, model_data, final_size) | |
| st.image(generated_label, caption="Generated Label Preview", width=520) | |
| img_buffer = io.BytesIO() | |
| generated_label.save(img_buffer, format="PNG") | |
| img_buffer.seek(0) | |
| st.sidebar.download_button( | |
| label="Download", | |
| data=img_buffer, | |
| file_name="AIEnergyScore.png", | |
| mime="image/png" | |
| ) | |
| st.sidebar.write("#### 3. Share your label! [Guidelines](https://huggingface.github.io/AIEnergyScore/#labelusage)") | |
| st.sidebar.markdown("<hr style='border: 1px solid gray; margin: 15px 0;'>", unsafe_allow_html=True) | |
| st.sidebar.write("### Key Links") | |
| st.sidebar.write("- [Leaderboard](https://huggingface.co/spaces/AIEnergyScore/Leaderboard)") | |
| st.sidebar.write("- [Submission Portal](https://huggingface.co/spaces/AIEnergyScore/submission_portal)") | |
| st.sidebar.write("- [FAQ](https://huggingface.github.io/AIEnergyScore/#faq)") | |
| st.sidebar.write("- [Documentation](https://huggingface.github.io/AIEnergyScore/#documentation)") | |
| def create_label_single_pass(background_image, model_data, final_size=(520, 728)): | |
| """ | |
| Resizes the background to 520×728, then draws text onto it. | |
| """ | |
| # 1. Resize background to final_size | |
| bg_resized = background_image.resize(final_size, Image.Resampling.LANCZOS) | |
| draw = ImageDraw.Draw(bg_resized) | |
| # 2. Load fonts at sizes appropriate for a 520×728 label | |
| try: | |
| title_font = ImageFont.truetype("Inter_24pt-Bold.ttf", size=27) | |
| details_font = ImageFont.truetype("Inter_18pt-Regular.ttf", size=23) | |
| energy_font = ImageFont.truetype("Inter_18pt-Medium.ttf", size=24) | |
| except Exception as e: | |
| st.error(f"Font loading failed: {e}") | |
| return bg_resized | |
| # 3. Place your text. | |
| # You may need to experiment with x/y coordinates or font sizes | |
| # to make it look right in 520×728. | |
| title_x, title_y = 33, 150 | |
| details_x, details_y = 480, 256 | |
| energy_x, energy_y = 480, 472 | |
| # Text 1 (title) | |
| draw.text((title_x, title_y), str(model_data['model']), font=title_font, fill="black") | |
| draw.text((title_x, title_y + 38), str(model_data['provider']), font=title_font, fill="black") | |
| # Text 2 (details) | |
| details_lines = [ | |
| str(model_data['date']), | |
| str(model_data['task']), | |
| str(model_data['hardware']) | |
| ] | |
| for i, line in enumerate(details_lines): | |
| bbox = draw.textbbox((0, 0), line, font=details_font) | |
| text_width = bbox[2] - bbox[0] | |
| # Right-justify the details text at details_x | |
| draw.text((details_x - text_width, details_y + i*47), line, font=details_font, fill="black") | |
| # Text 3 (energy) | |
| energy_text = str(model_data['energy']) | |
| bbox = draw.textbbox((0, 0), energy_text, font=energy_font) | |
| energy_text_width = bbox[2] - bbox[0] | |
| # Right-align the energy text at energy_x | |
| draw.text((energy_x - energy_text_width, energy_y), energy_text, font=energy_font, fill="black") | |
| return bg_resized | |
| if __name__ == "__main__": | |
| main() |