Update dataframe

app.py

@@ -41,6 +41,7 @@ from botocore.exceptions import NoCredentialsError
 import tempfile
 import io
 from PIL import Image
+from pandas import json_normalize
 # Images
 torch.hub.download_url_to_file('https://i.pinimg.com/564x/18/0b/00/180b00e454362ff5caabe87d9a763a6f.jpg', 'ejemplo1.jpg')
 torch.hub.download_url_to_file('https://i.pinimg.com/564x/3b/2f/d4/3b2fd4b6881b64429f208c5f32e5e4be.jpg', 'ejemplo2.jpg')
@@ -53,27 +54,11 @@ region = os.environ['region']
 def removeStr(string): 
   return string.replace(" ", "")
 
-def arrayLista(a,b,c,d):
-  x = re.findall("obo Mar", b)
-  y = re.findall("elica", b)
-  z = re.findall("elica", d)
-  if x:
-    b = 'Lobo marino'
-  if y:
-    b = 'Pelicano'
-  if z:
-    d = 'Pelicano'
-  if(b=='Lobo marino' or b=='Pelicano'):
-    strlist =[]
-    strlist2 =[]
-    strlist.append(removeStr(a))
-    strlist.append(b)
-    if d=='Pelicano':
-      strlist2.append(removeStr(c))
-      strlist2.append(d)
-    strlista = [strlist,strlist2]
-    df = pd.DataFrame(strlista,columns=['Cantidad','Especie'])
-    return df
+def arrayListax(json_data):
+  dict = json_data
+  df2 = json_normalize(dict['detail']) 
+  #df = pd.DataFrame(df2,columns=['Cantidad','Especie'])
+  return df2
 
 #Imagen temporal guardada en upload_file
 def tempFileJSON(img_file):
@@ -158,7 +143,7 @@ def yolo(size, iou, conf, im):
       fileImg = tempFileJSON(im_bytes)
       #Enviando la informacion al contador de especies
       results6 = qtyEspecies(results5,results3,fileImg)
-      lista2 = arrayLista(results3[19:21],results3[22:32], results3[34:36], results3[37:45])
+      lista2 = arrayListax(results6)
       return Image.fromarray(results2.ims[0]), lista2, results6
     except Exception as e:
       logging.error(e, exc_info=True)
@@ -171,7 +156,7 @@ 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", headers=['Cantidad','Especie'])  
+out3 = gr.outputs.Dataframe(type="pandas", label="Descripción", headers=['Cantidad','Especie'])  
 out4 = gr.outputs.JSON(label="JSON")
 #-------------- Text-----
 title = 'OceanApp'