Merge pull request #1 from archit-spec/dev

Dev

Dockerfile

@@ -1,8 +1,20 @@
-FROM python:3.11
+FROM python:3.8.10-slim
+
 WORKDIR /app
-COPY requirements.txt requirements.txt
-RUN pip install -r requirements.txt
+
+COPY poetry.lock pyproject.toml ./
+
+RUN pip install poetry && poetry config virtualenvs.create false
+
+RUN /root/.cargo/bin/uv pip install --no-cache -r requirements.txt
+
 COPY . .
+
 EXPOSE 5001
-CMD ["python", "app.py"]
+
+# Command to run the application (assuming it's a Flask app)
+CMD ["streamlit", "run","main.py"]  # Replace with your application's entry point if different
+
+# Alternative command for uvicorn (if your application uses it)
+# CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "5001"]
 

README.md

@@ -1,13 +1,14 @@
 #  Deeplearning based filebrowser (WIP):
 
-## image captioning demo 
-![demo for captioning](./demo.mp4)
+## filebrowser demo 
+![demo](https://youtu.be/CIXq6xz7tHc)
 
 - aim is to provide a better search in filebrowsers when the filebrowsere names are cryptic and it is hard to find an image or a document based on the standard search
 ## todo
-- make ui
-- make easily deoployable with docker and add onnx runtime or optimuim
-- add support for pdfs, and videos using sentence transformer embeddings and video captioning models
+- [x] Make UI
+- [ ] Make easily deployable with Docker and add ONNX Runtime or Optimuim
+- [ ] Add support for PDFs and videos using Sentence Transformer embeddings and video captioning models
+- [ ] Optimize using `joblib` cache
 
 
 ## to run. do:

main.py

@@ -0,0 +1,49 @@
+import streamlit as st
+import os
+from PIL import Image
+from src.captioning import ImageCaptioning
+
+def main():
+    """Main function of the Streamlit application."""
+    st.title("Image Explorer")
+
+    # Get directory path from user input or set default
+    default_dir = os.getcwd()  # Use current working directory as default
+    user_dir = st.text_input("Enter directory path:", default_dir)
+    if user_dir:
+        dir_path = user_dir
+    else:
+        dir_path = default_dir
+
+    # Check if directory exists
+    if not os.path.exists(dir_path):
+        st.error(f"Directory '{dir_path}' does not exist")
+        return
+
+    # Create an instance of ImageCaptioning and generate the index
+    image_captioning = ImageCaptioning()
+    image_dict = image_captioning.make_index(dir_path)
+
+    # Add search bar
+    search_term = st.text_input("Search images by description:", "")
+
+    # Filter images based on search term
+    filtered_images = [
+        (image_path, descriptions)
+        for image_path, descriptions in image_dict.items()
+        if any(search_term.lower() in description.lower() for description in descriptions)
+    ]
+
+    # Define CSS class (assuming you have a style.css file linked)
+    st.markdown(f"<link rel='stylesheet' href='path/to/your/style.css'>", unsafe_allow_html=True)
+
+    # Display images with descriptions and file paths
+    for image_path, descriptions in filtered_images:
+        st.image(Image.open(image_path))
+        st.markdown(f"<p class='caption-center'>Image Path: {image_path}</p>", unsafe_allow_html=True)
+        for description in descriptions:
+            st.markdown(f"<p class='caption-center'>Description: {description}</p>", unsafe_allow_html=True)
+
+if __name__ == "__main__":
+    main()
+