layout

analysis.ipynb

@@ -11,7 +11,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -301,9 +301,46 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 5,
       "metadata": {},
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Running on local URL:  http://127.0.0.1:7860\n",
+            "\n",
+            "To create a public link, set `share=True` in `launch()`.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+            ],
+            "text/plain": [
+              "<IPython.core.display.HTML object>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Keyboard interruption in main thread... closing server.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": []
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
       "source": [
         "from app import app\n",
         "\n",
@@ -350,7 +387,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.13"
+      "version": "3.1.0"
     }
   },
   "nbformat": 4,

app.py

@@ -5,7 +5,7 @@ from pdf2image import convert_from_path, convert_from_bytes
 
 def similarity_fn(document_image_1, document_image_2):
     xxx = 'BOTH' if document_image_1 and document_image_2 else 'ONE' if document_image_1 or document_image_2 else 'NONE'
-    return xxx
+    return gr.HTML(f'<pre>Similarity between the two documents: {xxx}<pre>', visible=True)
 
 def load_image(filename, page = 0):
     try:
@@ -61,11 +61,11 @@ def document_view(document_number: int):
 
 def app():
     title = 'Document Similarity Search Using Visual Layout Features'
-    description = "<h2>Document Similarity Search using Detectron2<h2>"
-    article = "<h4>More details, Links about this! - Document Similarity Search using Detectron2<h4>"
+    description = f"<h2>{title}<h2>"
     css = '''
     image { max-height="86vh" !important; }
     .center { display: flex; flex: 1 1 auto; align-items: center; align-content: center; justify-content: center; justify-items: center; }
+    .hr { width: 100%; display: block; padding: 0; margin: 0; background: gray; height: 4px;  border: none; }
   '''
     with gr.Blocks(title=title, css=css) as app:
         with gr.Row():
@@ -75,17 +75,15 @@ def app():
                 document_1_image = document_view(1)
             with gr.Column():
                 document_2_image = document_view(2)
-        with gr.Row():
-            # gr.HTML(value=article, elem_classes=['center'])
-            submit = gr.Button(value="Preview", variant="primary")
-            similarity_output = gr.HTML(value=article, elem_classes=['center'], visible=False)
+        gr.HTML('<hr/>', elem_classes=['hr'])
+        with gr.Row(elem_classes=['center']):
+            with gr.Column():
+                submit = gr.Button(value="Similarity", variant="primary")
+                reset = gr.Button(value="Reset", variant="secondary")
+            with gr.Column():
+                similarity_output = gr.HTML(visible=False)
             submit.click(
-                fn=lambda image: similarity_fn(image, just_image=False),
+                fn=similarity_fn,
                 inputs=[document_1_image, document_2_image],
                 outputs=[similarity_output])
-        
-        # threshold.change(
-        #     fn=lambda image, threshold: similarity_fn(image, threshold, just_image=False),
-        #     inputs=[document_1, threshold],
-        #     outputs=[annotated_document_image, message])
     return app.launch(debug=True)