Update app.py

app.py

@@ -114,8 +114,7 @@ with gr.Blocks() as iface:
     > `TransCheX` model consists of vision, language, and mixed-modality transformer layers for processing chest X-ray and their corresponding radiological reports within a unified framework. 
 
     I modified the architecture by varying the number of vision, language and mixed-modality layers and customizing the classification head. In addition, I added image preprocessing and more language processing modules.
-    - Image Preprocessing 
-        - 
+
     Finally, the model is pre-trained on the Open-I dataset and fine-tuned on modified and relabeled [SIIM-FISABIO-RSNA COVID-19 Detection](https://www.kaggle.com/competitions/siim-covid19-detection/data) and [VinBigData Chest X-ray Abnormalities Detection ](https://www.kaggle.com/competitions/vinbigdata-chest-xray-abnormalities-detection/data).
 
     ## Components
@@ -125,6 +124,7 @@ with gr.Blocks() as iface:
     - [scikit-image: Image processing in Python](https://scikit-image.org/): is a collection of algorithms for image processing. I used this module for all the image preprocessing.
     - [gradio](https://github.com/gradio-app/gradio):  is an open-source Python library that is used to build machine learning and data science demos and web applications. This demo is created by gradio. 
     - [Modal](https://modal.com/): is a end to end stack for cloud compute. This is used to deploy the model-service for subsequent fine-tuning on more datasets.
+    - [mage-ai/mage-ai: 🧙 A modern replacement for Airflow.](https://github.com/mage-ai/mage-ai) is a tool to build real-time and batch pipelines to **transform** data using Python, SQL, and R. Run, monitor, and **orchestrate** thousands of pipelines without losing sleep. I'm using this tool to build an online data processing pipeline.
 
     ## Dataset 
     The Open-I dataset provides a collection of 3,996 radiology reports with 8,121 associated images in PA, AP and lateral views. The 14 finding categories in this work include Atelectasis, Cardiomegaly, Consolidation, Edema, Enlarged-Cardiomediastinum, Fracture, Lung-Lesion, Lung-Opacity, No-Finding, Pleural-Effusion, Pleural-Other, Pneumonia, Pneumothorax and Support-Devices. More information can be found in this [link](https://openi.nlm.nih.gov/faq)
@@ -156,5 +156,14 @@ with gr.Blocks() as iface:
          model_predict,
          cache_examples=True,
     )
+    
+    gr.Markdown(
+    """## Todo/Doing
+    - TODO -- Fine-tuning on more datasets 
+    - Doing -- Add the object detection model, plan to use yolov5 
+    - Doing -- Build an online machine learning pipeline
+
+    """
+    )
         
-iface.launch()
+iface.launch()