Update dataframe and json

app.py

@@ -47,6 +47,34 @@ torch.hub.download_url_to_file('https://i.pinimg.com/564x/3b/2f/d4/3b2fd4b6881b6
 model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True, autoshape=True)  # local model  o google colab
 #model = torch.hub.load('path/to/yolov5', 'custom', path='/content/yolov56.pt', source='local')  # local repo
 
+def listJSON(a,b,c,d):
+      try:
+        strlist =[] 
+        strlist.append(a)
+        strlist.append(b)
+        strlist.append(c) 
+        if d =='Pelicano\nSp':
+          strlist.append('Pelicano')
+        else:
+          strlist.append(d)
+        json_string = json.dumps(strlist)
+        return json_string
+      except Exception as e:
+        logging.error(e, exc_info=True)
+
+def arrayLista(a,b):
+      try:
+        strlist =[{}]*1
+        strlist[0] = set()
+        strlist[0].add(a)
+        if b =='Pelicano\nSp':
+          strlist[0].add('Pelicano')
+        else:
+          strlist[0].add(b)
+        df = pd.DataFrame(strlist,columns=['Especie','Cantidad'])
+        return df
+      except Exception as e:
+        logging.error(e, exc_info=True)
 
 def yolo(size, iou, conf, im):
     try:
@@ -58,13 +86,14 @@ def yolo(size, iou, conf, im):
         
         model.conf = conf
 
-    
         results2 = model(im)  # inference
-    
         results2.render()  # updates results.imgs with boxes and labels
-        return Image.fromarray(results2.ims[0])
+        results3 = str(results2)
+        lista = listJSON(results3[0:9], results3[11:18] ,results3[19:20],results3[21:32])
+        lista2 = arrayLista(results3[19:20],results3[21:32])
+        return Image.fromarray(results2.ims[0]), lista2, lista
     except Exception as e:
-      logging.error(e, exc_info=True)
+        logging.error(e, exc_info=True)
 
 #------------ Interface-------------
 
@@ -74,6 +103,8 @@ in3 = gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.50, label='Umb
 in4 = gr.inputs.Image(type='pil', label="Original Image")
 
 out2 = gr.outputs.Image(type="pil", label="Identificación con Yolov5")
+out3 = gr.outputs.Dataframe(label="Descripción")   
+out4 = gr.outputs.JSON(label="JSON")
 #-------------- Text-----
 title = 'OceanApp'
 description = """
@@ -91,7 +122,7 @@ article ="<p style='text-align: center'><a href='' target='_blank'>Para mas info
           
 examples = [['640',0.45, 0.75,'ejemplo1.jpg'], ['640',0.45, 0.75,'ejemplo2.jpg']]
 
-iface = gr.Interface(yolo, inputs=[in1, in2, in3, in4], outputs=out2, title=title, description=description, article=article, examples=examples,theme="huggingface", analytics_enabled=False).launch(
+iface = gr.Interface(yolo, inputs=[in1, in2, in3, in4], outputs=[out2,out3,out4], title=title, description=description, article=article, examples=examples,theme="huggingface", analytics_enabled=False).launch(
     debug=True)
 
 iface.launch()