:tada: init

.github/workflows/check_size.yaml

@@ -0,0 +1,17 @@
+name: Check file size
+
+on:
+  pull_request:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check large files
+        uses: ActionsDesk/lfs-warning@v2.0
+        with:
+          filesizelimit: 10485760 # = 10MB, so we can sync to HF spaces

.github/workflows/sync_to_hub.yaml

@@ -0,0 +1,20 @@
+name: Sync to Hugging Face hub
+
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: git push https://nateraw:$HF_TOKEN@huggingface.co/spaces/nateraw/huggingpics-explorer main --force

README.md

@@ -0,0 +1,19 @@
+---
+title: huggingpics-explorer
+emoji: 🤗
+colorFrom: blue
+colorTo: red
+sdk: streamlit
+app_file: app.py
+pinned: false
+---
+
+# huggingpics-explorer
+
+[![Generic badge](https://img.shields.io/badge/🤗-Open%20In%20Spaces-blue.svg)](https://huggingface.co/spaces/nateraw/huggingpics-explorer)
+
+A streamlit app for exploring image search results from HuggingPics
+
+---
+
+Autogenerated using [this template](https://github.com/nateraw/spaces-template)

app.py

@@ -0,0 +1,46 @@
+import streamlit as st
+from huggingpics.data import get_image_urls_by_term
+
+
+def show_images_of_term(search_term, num_cols=5, num_rows=3):
+
+    # Get the image urls
+    # Arbitrarily adding 2 to make sure we have enough images in the event of a failed request
+    urls = get_image_urls_by_term(search_term, count=(num_rows * num_cols) + 2)
+
+    st.title(search_term)
+    for row_id in range(num_rows):
+        cols = st.columns(num_cols)
+        for col_id in range(num_cols):
+            cols[col_id].image(urls[row_id * num_cols + col_id], use_column_width=True)
+
+def explore():
+    with st.sidebar:
+        term_1 = st.sidebar.text_input('Search Term 1', value='shiba inu')
+        term_2 = st.sidebar.text_input('Search Term 2', value='husky')
+        term_3 = st.sidebar.text_input('Search Term 3', value='')
+        term_4 = st.sidebar.text_input('Search Term 4', value='')
+        term_5 = st.sidebar.text_input('Search Term 5', value='')
+
+        terms = [t for t in [term_1, term_2, term_3, term_4, term_5] if t]
+
+    for term in terms:
+        show_images_of_term(term)
+
+
+def create_dataset():
+    st.text("# Coming soon...")
+
+
+def main():
+    
+    with st.sidebar:
+        mode = st.sidebar.selectbox("Mode", ["Explore", "Create Dataset"])
+        st.sidebar.markdown("---")
+
+    _ = explore() if mode == "Explore" else create_dataset()
+
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+huggingpics