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import os
import pandas as pd
from PIL import Image
from itertools import islice
import earthview as ev # Your custom library
import gradio as gr
# Path to the first shard of the Satellogic dataset
filename = os.path.join("dataset", "satellogic", "train-00000-of-00065.parquet")
# Check if the file exists
if not os.path.isfile(filename):
raise FileNotFoundError(f"{filename} not found")
# Loads a dataset with pandas, this loads a single file
data = pd.read_parquet(filename)
# Global variables to manage state
current_image = None
current_metadata_index = 0
ratings = []
image_id = 0
bounds = []
timestamps = []
# Function to transform a metadata sample to bounds and timestamps
def item_to_bounds_timestamps(sample):
bounds_list = sample["metadata"]["bounds"]
timestamp_list = sample["metadata"]["timestamp"]
bounds = []
timestamps = []
for b, t in zip(bounds_list, timestamp_list):
bounds.append(b)
timestamps.append(t)
return bounds, timestamps
# Function to load and display the next image
def load_next_image():
global current_image, image_id, current_metadata_index, bounds, timestamps
if current_metadata_index >= len(data):
return None, "No more images", None
sample = data.iloc[current_metadata_index]
bounds_sample, timestamps_sample = item_to_bounds_timestamps(sample)
# Use earthview library to convert arrays to PIL images
sample = ev.item_to_images("satellogic", sample.to_dict())
current_image = sample["rgb"][0] # Get the first image
image_id += 1
return current_image, f"Image ID: {image_id}", bounds_sample[0]
# Function to handle rating submission
def submit_rating(rating, bounds_str):
global image_id, current_metadata_index, ratings, bounds, timestamps
ratings.append(rating)
bounds.append(bounds_str)
timestamps.append("timestamp") # Use a valid timestamp if available
current_metadata_index += 1
return load_next_image()
# Gradio Interface Layout
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
image_display = gr.Image(label="Satellite Image", type="pil")
image_id_display = gr.Textbox(label="Image ID")
bounds_display = gr.Textbox(label="Bounds")
load_button = gr.Button("Load Next Image")
load_button.click(fn=load_next_image, outputs=[image_display, image_id_display, bounds_display])
with gr.Column():
rating_radio = gr.Radio(["0", "1"], label="Rating (0 = No, 1 = Yes)")
submit_button = gr.Button("Submit Rating")
submit_button.click(fn=lambda rating, bounds_str: submit_rating(rating, bounds_str), inputs=[rating_radio, bounds_display], outputs=[image_display, image_id_display, bounds_display])
# Launch the Gradio interface
demo.launch() |