turn off example caching

gradio-ocsai-d.py

@@ -64,25 +64,32 @@ def classify_image(img_dict: dict):
     
     p = get_predictions(img.convert('RGB'))
 
-    score_round = str(np.round(p['originality'], 2))
-    label = f"Percentile: {p['percentile']}; Normalized Score: {score_round}"
-    label_df = pd.DataFrame({'y': [p['originality']], 'text': [label]})
-
-    rule = alt.Chart(label_df).mark_rule(
+    label = f"Percentile: {int(p['percentile'])}"
+    label_df = pd.DataFrame({'y': [p['originality']],
+                             'x': [p['percentile']],
+                             'text': [label]})
+
+    point = alt.Chart(label_df).mark_point(
+        shape='triangle',
+        size=200,
+        filled=True,
         color='red'
     ).encode(
+        x='x',
         y='y'
     )
     
     txt = alt.Chart(label_df).mark_text(
         align='left',
         baseline='middle',
-        dx=0, dy=-8
+        dx=10, dy=-10,
+        fontSize=14
     ).encode(
         y='y',
+        x='x',
         text='text'
     )
-    return base_chart + rule + txt
+    return base_chart + point + txt
 
 
 def update_editor(background, img_editor):
@@ -118,10 +125,8 @@ demo = gr.Interface(fn=classify_image,
                      outputs=gr.Plot(),
                      title="Ocsai-D",
                      description="Complete the drawing and classify the originality. Choose the brush icon below the image to start editing.\n\nModel from *A Comparison of Supervised and Unsupervised Learning Methods in Automated Scoring of Figural Tests of Creativity* ([preprint](http://dx.doi.org/10.13140/RG.2.2.26865.25444)).\n\nExamples are from MTCI ([Barbot 2018](https://pubmed.ncbi.nlm.nih.gov/30618952/)).",
-                     examples=gr.Examples(
-                         examples=examples,
-                         label="Prompts"
-                         )
+                     examples=examples,
+                     cache_examples=False
                      )
 
 demo.launch(debug=True)