test

app.py

@@ -1,10 +1,108 @@
 import gradio as gr
 
-def single_inference():
-    pass
+def single_inference_iit(head_img, head_id, tail_img, tail_id, question_txt, question_id):
+    return question_txt
+
+def single_inference_tti(head_txt, head_id, tail_txt, tail_id, question_img, question_id):
+    return head_txt
+
+def blended_inference_iti(head_img, head_id, tail_txt, tail_id, question_img, question_id):
+    return tail_txt
+
+def single_tab_iit():
+    with gr.Column():
+        gr.Markdown(""" $(I_h, I_t) : (T_q, ?)$
+                    """)
+        with gr.Row():
+            with gr.Column():
+                head_image = gr.Image(type='pil', label="Head Image")
+                head_ent = gr.Textbox(lines=1, label="Head Entity")
+            with gr.Column():
+                tail_image = gr.Image(type='pil', label="Tail Image")
+                tail_ent = gr.Textbox(lines=1, label="Tail Entity")
+            with gr.Column():
+                question_text = gr.Textbox(lines=1, label="Question Name")
+                question_ent = gr.Textbox(lines=1, label="Question Entity")
+                
+    submit_btn = gr.Button("Submit")
+    output_text = gr.Textbox(label="Output")
+    
+    submit_btn.click(fn=single_inference_iit, 
+        inputs=[head_image, head_ent, tail_image, tail_ent, question_text, question_ent], 
+        outputs=[output_text])
+        
+    examples=[['examples/qinghai_lake.png', 'Q201294', 'examples/inland_lake.png', 'Q31805992', "campaign", 'Q18812548']]
+    ex = gr.Examples(
+        examples=examples, 
+        fn=single_inference_iit, 
+        inputs=[head_image, head_ent, tail_image, tail_ent, question_text, question_ent], 
+        outputs=[output_text],
+        cache_examples=True, 
+        run_on_click=True
+    )
+   
+def single_tab_tti():    
+    with gr.Column():
+        gr.Markdown(""" $(T_h, T_t) : (I_q, ?)$
+                    """)
+        with gr.Row():
+            with gr.Column():
+                head_text = gr.Textbox(lines=1, label="Head Name")
+                head_ent = gr.Textbox(lines=1, label="Head Entity")
+            with gr.Column():
+                tail_text = gr.Textbox(lines=1, label="Tail Name")
+                tail_ent = gr.Textbox(lines=1, label="Tail Entity")
+            with gr.Column():
+                question_text = gr.Image(type='pil', label="Question Image")
+                question_ent = gr.Textbox(lines=1, label="Question Entity")
+    submit_btn = gr.Button("Submit")
+    output_text = gr.Textbox(label="Output")
+    
+    submit_btn.click(fn=single_inference_iit, 
+        inputs=[head_text, head_ent, tail_text, tail_ent, question_text, question_ent], 
+        outputs=[output_text])
+        
+    examples=[['qinghai_lake', 'Q201294', 'inland_lake', 'Q31805992', 'examples/qinghai_lake.png', 'Q18812548']]
+    ex = gr.Examples(
+        examples=examples, 
+        fn=single_inference_iit, 
+        inputs=[head_text, head_ent, tail_text, tail_ent, question_text, question_ent], 
+        outputs=[output_text],
+        cache_examples=True, 
+        run_on_click=True
+    )
+    
+def blended_tab_iti():
+    with gr.Column():
+        gr.Markdown(""" $(I_h, T_t) : (I_q, ?)$
+                    """)
+        with gr.Row():
+            with gr.Column():
+                head_image = gr.Image(type='pil', label="Head Image")
+                head_ent = gr.Textbox(lines=1, label="Head Entity")
+            with gr.Column():
+                tail_txt = gr.Textbox(lines=1, label="Tail Name")
+                tail_ent = gr.Textbox(lines=1, label="Tail Entity")
+            with gr.Column():
+                question_image = gr.Image(type='pil', label="Question Image")
+                question_ent = gr.Textbox(lines=1, label="Question Entity")
+    submit_btn = gr.Button("Submit")
+    output_text = gr.Textbox(label="Output")
+    
+    submit_btn.click(fn=single_inference_iit, 
+        inputs=[head_image, head_ent, tail_txt, tail_ent, question_image, question_ent], 
+        outputs=[output_text])
+        
+    examples=[['examples/qinghai_lake.png', 'Q201294', 'inland_lake', 'Q31805992', 'examples/inland_lake.png', 'Q18812548']]
+    ex = gr.Examples(
+        examples=examples, 
+        fn=single_inference_iit, 
+        inputs=[head_image, head_ent, tail_txt, tail_ent, question_image, question_ent], 
+        outputs=[output_text],
+        cache_examples=True, 
+        run_on_click=True
+    )
 
-def blended_inference():
-    pass
 
 TITLE = """MKG Analogy"""
 
@@ -13,43 +111,13 @@ with gr.Blocks() as block:
         gr.HTML(TITLE)
 
         with gr.Tab("Single Analogical Reasoning"):
-            with gr.Column():
-                gr.Markdown(""" $(I_h, I_t) : (T_q, ?)$
-                            """)
-                with gr.Row():
-                    with gr.Column():
-                        head_image = gr.Image(type='pil', label="Head Image")
-                        head_ent = gr.Textbox(lines=1, label="Head Entity")
-                    with gr.Column():
-                        tail_image = gr.Image(type='pil', label="Tail Image")
-                        tail_ent = gr.Textbox(lines=1, label="Tail Entity")
-                    with gr.Column():
-                        question_text = gr.Textbox(lines=1, label="Question Name")
-                        question_ent = gr.Textbox(lines=1, label="Question Entity")
-            submit_btn = gr.Button("Submit")
-            output_text = gr.Textbox(label="Output")
-
-            # examples=[['example01.jpg', MODELS[0], 'best'], ['example02.jpg', MODELS[0], 'best']]
-            # ex = gr.Examples(
-            #     examples=examples, 
-            #     fn=image_to_prompt, 
-            #     inputs=[input_image, input_model, input_mode], 
-            #     outputs=[output_text, share_button, community_icon, loading_icon], 
-            #     cache_examples=True, 
-            #     run_on_click=True
-            # )
-            # ex.dataset.headers = [""]
+            single_tab_iit()
+            single_tab_tti()
 
         with gr.Tab("Blended Analogical Reasoning"):
-            pass
-        
+            blended_tab_iti()
+    
         # gr.HTML(ARTICLE)
-
-    # submit_btn.click(
-    #     fn=image_to_prompt, 
-    #     inputs=[input_image, input_model, input_mode], 
-    #     outputs=[output_text, share_button, community_icon, loading_icon]
-    # )
-    # share_button.click(None, [], [], _js=None)
+        
 
 block.queue(max_size=64).launch(enable_queue=True)