Update app lists

app.py

@@ -51,34 +51,34 @@ region = os.environ['region']
 
 # Envio de imagenes a S3
 def upload_file(file_name, bucket=None, object_name=None):
-    """Upload a file to an S3 bucket
-
-    :param file_name: File to upload
-    :param bucket: Bucket to upload to
-    :param object_name: S3 object name. If not specified then file_name is used
-    :return: Json if file was uploaded, else False
-    """
-    # If S3 object_name was not specified, use file_name
-    if object_name is None:
-        object_name = os.path.basename(file_name+".jpg")
-    if bucket is None:
-        bucket = 'oceanapp'
-    s3_client = boto3.client('s3',aws_access_key_id=aws_access_key_id,aws_secret_access_key=aws_secret_access_key)
-    aws_region = boto3.session.Session().region_name
-    # Upload the file
-    try:
-        with open(file_name, "rb") as f:
-          response = s3_client.upload_fileobj(f, bucket, object_name)
-          s3_url = f"https://{bucket}.s3.amazonaws.com/{object_name}"
-          stado = '"url_details":[{"statusCode":200, "s3_url":"'+s3_url+'"}]'
-        print(s3_url)
-    except FileNotFoundError:
-        print("The file was not found")
-        return False
-    except NoCredentialsError as e:
-        logging.error(e)
-        return False
-    return stado
+  """Upload a file to an S3 bucket
+
+  :param file_name: File to upload
+  :param bucket: Bucket to upload to
+  :param object_name: S3 object name. If not specified then file_name is used
+  :return: Json if file was uploaded, else False
+  """
+  # If S3 object_name was not specified, use file_name
+  if object_name is None:
+    object_name = os.path.basename(file_name+".jpg")
+  if bucket is None:
+    bucket = 'oceanapp'
+  s3_client = boto3.client('s3',aws_access_key_id=aws_access_key_id,aws_secret_access_key=aws_secret_access_key)
+  aws_region = boto3.session.Session().region_name
+  # Upload the file
+  try:
+    with open(file_name, "rb") as f:
+      response = s3_client.upload_fileobj(f, bucket, object_name)
+      s3_url = f"https://{bucket}.s3.amazonaws.com/{object_name}"
+      stado = '"url_details":[{"statusCode":200, "s3_url":"'+s3_url+'"}]'
+    print(s3_url)
+  except FileNotFoundError:
+    print("The file was not found")
+    return False
+  except NoCredentialsError as e:
+    logging.error(e)
+    return False
+  return stado
 
 #Imagen temporal guardada en upload_file
 def tempFileJSON(img_file):
@@ -90,53 +90,53 @@ def tempFileJSON(img_file):
     return uf
 
 def removeStr(string): 
-    return string.replace(" ", "")
-
-# Model
-model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True, autoshape=True)  # local model  o google colab
+  return string.replace(" ", "")
 
 def listJSON(a,b,c,d,e,f,resImg):
-      x = re.findall("obo mar", d)
-      y = re.findall("elica", d)
-      z = re.findall("elica", f)
-      if x:
-        d = 'Lobo marino'
-      if y:
-        d = 'Pelicano'
-      if z:
-        f = 'Pelicano'
-      if(d=='Lobo marino' or d=='Pelicano'):
-        if d =='Pelicano\nSp' or d =='Pelicano\nS':
-          d = 'Pelicano'
-        if f!='Pelicano':
-          strlista = '"detail":[{"quantity":"'+str(removeStr(c))+'","description":"'+str(d)+'"}]'
-        else:
-          strlista = '"detail":[{"quantity":"'+str(removeStr(c))+'","description":"'+str(d)+'"},{"quantity":"'+str(removeStr(e))+'","description":"'+str(f)+'"}]'
-        strlist = '{"image":"'+str(removeStr(a))+'","size":"'+str(removeStr(b))+'",'+strlista+','+resImg+'}'
-        json_string = json.loads(strlist)
-        return json_string
+  x = re.findall("obo mar", d)
+  y = re.findall("elica", d)
+  z = re.findall("elica", f)
+  if x:
+    d = 'Lobo marino'
+  if y:
+    d = 'Pelicano'
+  if z:
+    f = 'Pelicano'
+  if(d=='Lobo marino' or d=='Pelicano'):
+    if d =='Pelicano\nSp' or d =='Pelicano\nS':
+      d = 'Pelicano'
+    if f!='Pelicano':
+      strlista = '"detail":[{"quantity":"'+str(removeStr(c))+'","description":"'+str(d)+'"}]'
+    else:
+      strlista = '"detail":[{"quantity":"'+str(removeStr(c))+'","description":"'+str(d)+'"},{"quantity":"'+str(removeStr(e))+'","description":"'+str(f)+'"}]'
+    strlist = '{"image":"'+str(removeStr(a))+'","size":"'+str(removeStr(b))+'",'+strlista+','+resImg+'}'
+    json_string = json.loads(strlist)
+    return json_string
 
 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
+  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'])
+    print(df)
+    return df
+# Model
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True, autoshape=True)  # local model  o google colab
 
 def yolo(size, iou, conf, im):
     try: