Spaces:
Sleeping
Sleeping
File size: 3,637 Bytes
465c443 63711ea 7d5835f 80acacc 7d5835f 63711ea 5ec1d6a 7c425bb 09f8048 8e142ab 09f8048 8e142ab 09f8048 8e142ab 09f8048 7d5835f 8e142ab 7d5835f 8e142ab 7d5835f 8e142ab 7d5835f 8e142ab 7d5835f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
import gradio as gr
import earthview as ev
import utils
import random
import pandas as pd
import os
from itertools import islice
# Configuration
chunk_size = 100 # Size of the chunks to shuffle
label_file = os.path.join(os.path.dirname(__file__), "labels.csv") # Save CSV in the same directory as the script
# Load the Satellogic dataset (streaming)
dataset = ev.load_dataset("satellogic", streaming=True)
data_iter = iter(dataset)
shuffled_chunk = [] # Initialize an empty list to hold the current chunk
chunk_iter = None # Initialize the chunk iterator
# Initialize or load labels DataFrame
if os.path.exists(label_file):
labels_df = pd.read_csv(label_file)
else:
labels_df = pd.DataFrame(columns=["image_id", "bounds", "rating", "google_maps_link"])
def get_next_image():
global data_iter, labels_df, shuffled_chunk, chunk_iter
while True:
# If we don't have a current chunk or it's exhausted, get a new one
if not shuffled_chunk or chunk_iter is None:
chunk = list(islice(data_iter, chunk_size))
if not chunk: # If the dataset is exhausted, reset the iterator
print("Dataset exhausted, resetting iterator.")
data_iter = iter(ev.load_dataset("satellogic", streaming=True))
chunk = list(islice(data_iter, chunk_size))
if not chunk:
print("Still no data after reset.")
return None, "Dataset exhausted", None, None
random.shuffle(chunk)
shuffled_chunk = chunk
chunk_iter = iter(shuffled_chunk)
try:
sample = next(chunk_iter)
sample = ev.item_to_images("satellogic", sample)
image = sample["rgb"][0]
metadata = sample["metadata"]
bounds = metadata["bounds"]
google_maps_link = utils.get_google_map_link(sample, "satellogic")
image_id = str(bounds)
if image_id not in labels_df["image_id"].values:
return image, image_id, bounds, google_maps_link
except StopIteration:
# Current chunk is exhausted, reset chunk variables to get a new one in the next iteration
shuffled_chunk = []
chunk_iter = None
def rate_image(image_id, bounds, rating):
global labels_df
new_row = pd.DataFrame(
{
"image_id": [image_id],
"bounds": [bounds],
"rating": [rating],
"google_maps_link": [""], # this isn't necessary to pass to the function since we aren't updating it here.
}
)
labels_df = pd.concat([labels_df, new_row], ignore_index=True)
labels_df.to_csv(label_file, index=False)
next_image, next_image_id, next_bounds, next_google_maps_link = get_next_image()
return next_image, next_image_id, next_bounds, next_google_maps_link
# Gradio interface
iface = gr.Interface(
fn=rate_image,
inputs=[
gr.Textbox(label="Image ID", visible=False),
gr.Textbox(label="Bounds", visible=False),
gr.Radio(["Cool", "Not Cool"], label="Rating"),
#gr.Textbox(label="Google Maps Link"), # Remove google maps link as an input
],
outputs=[
gr.Image(label="Satellite Image"),
gr.Textbox(label="Image ID", visible=False),
gr.Textbox(label="Bounds", visible=False),
gr.Textbox(label="Google Maps Link", visible=True), # Add google maps link as an output
],
title="TerraNomaly - Satellite Image Labeling",
description="Rate satellite images as 'Cool' or 'Not Cool'.",
live=False,
)
iface.launch(
share=True
) |