flag returns csv instead txt

Test Keras.ipynb

@@ -9,9 +9,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -23,7 +32,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -54,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 14,
    "metadata": {
     "scrolled": false
    },
@@ -63,9 +72,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Closing existing server...\n",
       "NOTE: Gradio is in beta stage, please report all bugs to: contact.gradio@gmail.com\n",
-      "Model is running locally at: http://localhost:7860/\n",
-      "Model available publicly for 8 hours at: https://c0097190.gradio.app/\n"
+      "Model is running locally at: http://localhost:7861/\n",
+      "Unable to create public link for interface, please check internet connection or try restarting python interpreter.\n"
      ]
     },
     {
@@ -75,30 +85,48 @@
        "        <iframe\n",
        "            width=\"1000\"\n",
        "            height=\"500\"\n",
-       "            src=\"http://localhost:7860/\"\n",
+       "            src=\"http://localhost:7861/\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "text/plain": [
-       "<IPython.lib.display.IFrame at 0x22abbdace10>"
+       "<IPython.lib.display.IFrame at 0x26c65349978>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "''"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "io.launch(inline=True, inbrowser=False, share=True, validate=False);"
+    "io.launch(inline=True, inbrowser=False, share=True, validate=False)\n",
+    ";"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.6 (tensorflow)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "tensorflow"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -110,7 +138,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.7.1"
   }
  },
  "nbformat": 4,

gradio/inputs.py

@@ -9,6 +9,7 @@ from gradio import preprocessing_utils, validation_data
 import numpy as np
 from PIL import Image, ImageOps
 import datetime
+import csv
 
 # Where to find the static resources associated with each template.
 BASE_INPUT_INTERFACE_TEMPLATE_PATH = 'templates/input/{}.html'
@@ -110,7 +111,7 @@ class Sketchpad(AbstractInput):
         timestamp = datetime.datetime.now()
         im.save(f'gradio-flagged/{timestamp.strftime("%Y-%m-%d %H-%M-%S")}.png', 'PNG')
         return None
-    
+
 
 class Webcam(AbstractInput):
     def __init__(self, preprocessing_fn=None, image_width=224, image_height=224, num_channels=3):
@@ -202,13 +203,20 @@ class ImageUpload(AbstractInput):
             array = im.reshape(1, self.image_width, self.image_height, self.num_channels)
         return array
 
-    def rebuild_flagged(self, inp):
+    def rebuild_flagged(self, msg):
         """
         Default rebuild method to decode a base64 image
         """
+        inp = msg['data']['input']
         im = preprocessing_utils.encoding_to_image(inp)
         timestamp = datetime.datetime.now()
         im.save(f'gradio-flagged/{timestamp.strftime("%Y-%m-%d %H-%M-%S")}.png', 'PNG')
+        f = open('gradio-flagged/gradio-flagged.csv','a+')
+        fields = [timestamp.strftime("%Y-%m-%d %H-%M-%S"),msg['data']['output']]
+        writer = csv.writer(f)
+        writer.writerow(fields)
+        f.close()
+
         return None
 
 class CSV(AbstractInput):

gradio/interface.py

@@ -136,7 +136,7 @@ class Interface:
                     f.write(str(msg['data']))
                     f.close()
                     inp = msg['data']['input']
-                    self.input_interface.rebuild_flagged(inp)
+                    self.input_interface.rebuild_flagged(msg)
 
             except websockets.exceptions.ConnectionClosed:
                 pass