text2video

README.md

@@ -4,7 +4,7 @@
 colorFrom: indigo
 colorTo: blue
 sdk: gradio
-app_file: Source Code/app.py
+app_file: app.py
 pinned: false
 license: mit
 short_description: Neural video studio using latent diffusion & cross attention
@@ -23,7 +23,7 @@   # Zero-Shot Video Generation
 
   A zero-shot neural synthesis studio leveraging latent diffusion models and cross-frame attention to synthesize temporally consistent video sequences directly from unconstrained textual prompts.
 
-  **[Source Code](Source%20Code/)**  ·  **[Project Report](https://github.com/Amey-Thakur/MACHINE--LEARNING/blob/main/ML%20Project/Zero-Shot%20Video%20Generation%20Project%20Report.pdf)**  ·  **[Video Demo](https://youtu.be/za9hId6UPoY)**  ·  **[Live Demo](https://huggingface.co/spaces/ameythakur/Zero-Shot-Video-Generation)**
+  **[Source Code](Source Code/)**  ·  **[Project Report](https://github.com/Amey-Thakur/MACHINE--LEARNING/blob/main/ML%20Project/Zero-Shot%20Video%20Generation%20Project%20Report.pdf)**  ·  **[Video Demo](https://youtu.be/za9hId6UPoY)**  ·  **[Live Demo](https://huggingface.co/spaces/ameythakur/Zero-Shot-Video-Generation)**
 
   <br>
 
@@ -240,7 +240,7 @@ ## Usage Guidelines
 This repository is openly shared to support learning and knowledge exchange across the academic community.
 
 **For Students**  
-Use this project as reference material for understanding **Neural Video Synthesis**, **Diffusion Models**, and **temporal latent interpolation**. The source code is explicitly annotated to facilitate self-paced learning and exploration of **Python-based generative deep learning pipelines**.
+Use this project as reference material for understanding **Neural Video Synthesis**, **Diffusion Models**, and **temporal latent interpolation**. The Source Code is explicitly annotated to facilitate self-paced learning and exploration of **Python-based generative deep learning pipelines**.
 
 **For Educators**  
 This project may serve as a practical lab example or supplementary teaching resource for **Machine Learning**, **Computer Vision**, and **Generative AI** courses. Attribution is appreciated when utilizing content.
@@ -310,3 +310,4 @@   ### 🎓 [MEng Computer Engineering Repository](https://github.com/Amey-Thakur
   *Semester-wise curriculum, laboratories, projects, and academic notes.*
 
 </div>
+

app.py

@@ -8,8 +8,7 @@ sys.path.insert(0, source_dir)
 # Change the current working directory to 'Source Code' so relative files like style.css are found
 os.chdir(source_dir)
 
-# Now, we just run the original app.py
-from app import demo
-
-if __name__ == "__main__":
-    pass
+# Import the main app logic
+# In Source Code/app.py, the launch() method is automatically called 
+# when 'on_huggingspace' is True. Simply importing it triggers the deployment.
+import app