test gallery

app.py

@@ -1,7 +1,50 @@
+from pathlib import Path
+import os
 import gradio as gr
+from gradio.components.gallery import GalleryImageType
+import datasets
+from datasets import load_dataset
+from huggingface_hub import HfApi, HfFileSystem, login
+from dotenv import load_dotenv
 
-def greet(name):
-    return "Hello " + name + "!!"
+load_dotenv()
+HF_TOKEN = os.getenv('HF_TOKEN')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+login(token=HF_TOKEN, add_to_git_credential=True)
+
+
+def stream_dataset_from_hub(split):
+    dataset = load_dataset('mcarthuradal/arm-unicef',
+                           data_dir='images',
+                           split=split,
+                           streaming=True)
+    return dataset
+
+
+dataset = stream_dataset_from_hub('train')
+
+
+def get_images(path: str | Path) -> list[GalleryImageType]:
+    # filenames = os.listdir(path)
+
+    # image_names = [filename for filename in filenames if filename.endswith('.tif')]
+    n = 50
+    image_batch = dataset.iter(n)
+
+    yield image_batch['image']
+
+
+iface = gr.Interface(fn=get_images,
+                     outputs='gallery',
+                     title='Aerial Images Gallery',
+                     description='A gallery of the train and test data to be used without annotations',
+                     analytics_enabled=False,
+                     allow_flagging='never', )
+gr.Gallery(columns=5,
+           rows=10,
+           min_width=500,
+           allow_preview=True,
+           show_download_button=False,
+           show_share_button=False)
+
+iface.launch(inbrowser=True)