Update app.py

app.py

@@ -47,8 +47,10 @@ for k,v in id2label.items():
   else:
     label2color[v[2:]]=label_color[k]
 
+
 processor = AutoProcessor.from_pretrained("microsoft/layoutlmv3-base", apply_ocr=True,lang=lang)
-model = AutoModelForTokenClassification.from_pretrained("atatavana/layoutlm_manifesto_bigdataset")
+model = AutoModelForTokenClassification.from_pretrained("alitavanaali/music_layoutlmv3_model")
+feature_extractor = LayoutLMv3FeatureExtractor(apply_ocr=True,lang=lang)
 
 
 def unnormalize_box(bbox, width, height):
@@ -406,7 +408,7 @@ css = """.output_image, .input_image {height: 600px !important}"""
 #examples = [["461BHH69.PDF"],["AP-481-RF.PDF"],["DP-095-ML.PDF"],["DQ-231-LL.PDF"],["FK-941-ET.PDF"], ["FL-078-NH.PDF"]
 #              ,["14ZZ69.PDF"],["74BCA69.PDF"],["254BEG69.PDF"],["761BJQ69.PDF"],["AB-486-EH.PDF"],["AZ-211-ZA.PDF"], ["CY-073-YV.PDF"]]
 # ["744BJQ69.PDF"], ['tarros_2.jpg'],
-#examples = [['test1.jpg'], ['doc1.pdf'], ['doc1.2.pdf']]
+examples = [['test1.jpg'], ['doc1.pdf'], ['doc1.2.pdf']]
 
 
 iface = gr.Interface(fn=completepreprocess,
@@ -416,7 +418,7 @@ iface = gr.Interface(fn=completepreprocess,
                      outputs=[gr.outputs.Image(type="pil", label="annotated image"),"dataframe"] ,
                      title=title,
                      description=description,
-                     #examples=examples,
+                     examples=examples,
                      css=css,
                      analytics_enabled = True, enable_queue=True)