Update app.py

app.py

@@ -6,75 +6,9 @@ import pandas as pd
 import os
 from itertools import islice
 
-# Configuration
-chunk_size = 100  # Size of the chunks to shuffle
-label_file = "labels.csv"
+# ... (rest of your code)
 
-# 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, google_maps_link):
-    global labels_df
-
-    new_row = pd.DataFrame(
-        {
-            "image_id": [image_id],
-            "bounds": [bounds],
-            "rating": [rating],
-            "google_maps_link": [google_maps_link],
-        }
-    )
-    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 (no changes needed here)
+# Gradio interface (remove initial_outputs from launch)
 iface = gr.Interface(
     fn=rate_image,
     inputs=[
@@ -94,14 +28,8 @@ iface = gr.Interface(
     live=False,
 )
 
-initial_image, initial_image_id, initial_bounds, initial_google_maps_link = get_next_image()
+# initial_image, initial_image_id, initial_bounds, initial_google_maps_link = get_next_image() # You don't need to call this here
 
 iface.launch(
-    share=True,
-    initial_outputs=[
-        initial_image,
-        initial_image_id,
-        initial_bounds,
-        initial_google_maps_link,
-    ],
+    share=True  # Only include valid launch arguments
 )