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import streamlit as st | |
import pandas as pd | |
from PIL import Image, ImageDraw, ImageFont | |
import io | |
def main(): | |
# Sidebar for dropdown, buttons, and instructions | |
st.sidebar.title("AI Energy Score Label Generator") | |
st.sidebar.write("### Instructions:") | |
st.sidebar.write("1. Select a model from the dropdown.") | |
st.sidebar.write("2. Review the label preview.") | |
st.sidebar.write("3. Download the label as a PNG.") | |
st.sidebar.markdown("[Learn more about AI Energy Scores](https://example.com)") | |
# Read Data from 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 | |
# Ensure the CSV has required 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 | |
# Dropdown for selecting a model | |
model_options = data_df["model"].unique().tolist() | |
selected_model = st.sidebar.selectbox("Select a Model:", model_options) | |
# Filter the data for the selected model | |
model_data = data_df[data_df["model"] == selected_model].iloc[0] | |
# Dynamically select the background image based on the score | |
try: | |
score = int(model_data["score"]) # Convert to int | |
background_path = f"{score}.png" # E.g., "1.png", "2.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 | |
# Generate the label with text | |
generated_label = create_label(background, model_data) | |
# Display the label | |
st.image(generated_label, caption="Generated Label Preview") | |
# Download button for the label | |
img_buffer = io.BytesIO() | |
generated_label.save(img_buffer, format="PNG") | |
img_buffer.seek(0) | |
st.sidebar.download_button( | |
label="Download Label as PNG", | |
data=img_buffer, | |
file_name="AIEnergyScore.png", | |
mime="image/png" | |
) | |
def create_label(background_image, model_data): | |
""" | |
Create the label image by adding text from model_data to the background image. | |
""" | |
label_img = background_image.convert("RGBA") | |
draw = ImageDraw.Draw(label_img) | |
# Load the Inter variable font (no LAYOUT_RAQM) | |
try: | |
inter_font_path = "Inter-VariableFont_opsz,wght.ttf" | |
title_font = ImageFont.truetype(inter_font_path, 16) # Bold for title | |
details_font = ImageFont.truetype(inter_font_path, 12) # Medium for details | |
energy_font = ImageFont.truetype(inter_font_path, 14) # Medium for energy | |
except Exception as e: | |
st.error(f"Font loading failed: {e}") | |
return label_img | |
# Define positions for each text group | |
title_x, title_y = 20, 20 # Top-left corner for title | |
details_x, details_y = label_img.width - 20, 20 # Top-right corner for details | |
energy_x, energy_y = label_img.width // 2, label_img.height - 50 # Center-bottom for energy | |
# Group 1: Title (Left-Justified) | |
draw.text((title_x, title_y), f"Model: {model_data['model']}", font=title_font, fill="black") | |
draw.text((title_x, title_y + 25), f"Provider: {model_data['provider']}", font=title_font, fill="black") | |
# Group 2: Details (Right-Justified) | |
details_lines = [ | |
f"Date: {model_data['date']}", | |
f"Task: {model_data['task']}", | |
f"Hardware: {model_data['hardware']}" | |
] | |
for i, line in enumerate(details_lines): | |
# Use textbbox to calculate text width | |
bbox = draw.textbbox((0, 0), line, font=details_font) | |
text_width = bbox[2] - bbox[0] # Right - Left | |
draw.text((details_x - text_width, details_y + i * 20), line, font=details_font, fill="black") | |
# Group 3: Energy (Bottom-Center) | |
energy_text = f"Energy: {model_data['energy']}" | |
bbox = draw.textbbox((0, 0), energy_text, font=energy_font) | |
energy_text_width = bbox[2] - bbox[0] | |
draw.text((energy_x - energy_text_width // 2, energy_y), energy_text, font=energy_font, fill="black") | |
return label_img | |
if __name__ == "__main__": | |
main() | |