added always_flag=False

gradio/inputs.py

@@ -122,9 +122,9 @@ class Sketchpad(AbstractInput):
         """
         Default rebuild method to decode a base64 image
         """
-        inp = msg['data']['input']
-        im = preprocessing_utils.decode_base64_to_image(inp)
-        timestamp = time.time()*1000
+
+        im = preprocessing_utils.decode_base64_to_image(msg)
+        timestamp = int(time.time()*1000)
         filename = f'input_{timestamp}.png'
         im.save(f'{dir}/{filename}', 'PNG')
         return filename
@@ -197,11 +197,10 @@ class Textbox(AbstractInput):
         """
         Default rebuild method for text saves it .txt file
         """
-        inp = msg['data']['input']
         timestamp = time.time()*1000
         filename = f'input_{timestamp}.png'
         with open(f'{dir}/{filename}.txt','w') as f:
-            f.write(inp)
+            f.write(msg)
         return filename
 
     def get_sample_inputs(self):
@@ -251,8 +250,7 @@ class ImageUpload(AbstractInput):
         """
         Default rebuild method to decode a base64 image
         """
-        inp = msg['data']['input']
-        im = preprocessing_utils.decode_base64_to_image(inp)
+        im = preprocessing_utils.decode_base64_to_image(msg)
         timestamp = time.time()*1000
         filename = f'input_{timestamp}.png'
         im.save(f'{dir}/{filename}', 'PNG')
@@ -283,8 +281,7 @@ class CSV(AbstractInput):
         """
         Default rebuild method for csv
         """
-        inp = msg['data']['inp']
-        return json.loads(inp)
+        return json.loads(msg)
 
 
 class Microphone(AbstractInput):
@@ -304,8 +301,7 @@ class Microphone(AbstractInput):
         """
         Default rebuild method for csv
         """
-        inp = msg['data']['inp']
-        return json.loads(inp)
+        return json.loads(msg)
 
 
 # Automatically adds all subclasses of AbstractInput into a dictionary (keyed by class name) for easy referencing.

gradio/interface.py

@@ -47,6 +47,7 @@ class Interface:
         postprocessing_fns=None,
         verbose=True,
         saliency=None,
+        always_flag=False
     ):
         """
         :param inputs: a string or `AbstractInput` representing the input interface.
@@ -99,6 +100,7 @@ class Interface:
         self.simple_server = None
         self.hash = random.getrandbits(32)
         self.saliency = saliency
+        self.always_flag = always_flag
 
     @staticmethod
     def _infer_model_type(model):

gradio/networking.py

@@ -194,6 +194,16 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
                     import numpy as np
                     saliency = interface.saliency(interface, interface.model_obj, raw_input, processed_input, prediction, processed_output)
                     output['saliency'] = saliency.tolist()
+                if interface.always_flag:
+                    msg = json.loads(data_string)
+                    flag_dir = os.path.join(FLAGGING_DIRECTORY, str(interface.hash))
+                    os.makedirs(flag_dir, exist_ok=True)
+                    output_flag = {'input': interface.input_interface.rebuild_flagged(flag_dir, msg['data']),
+                              'output': interface.output_interface.rebuild_flagged(flag_dir, processed_output),
+                              }
+                    with open(os.path.join(flag_dir, FLAGGING_FILENAME), 'a+') as f:
+                        f.write(json.dumps(output_flag))
+                        f.write("\n")
 
                 # Prepare return json dictionary.
                 self.wfile.write(json.dumps(output).encode())
@@ -202,10 +212,10 @@ def serve_files_in_background(interface, port, directory_to_serve=None):
                 self._set_headers()
                 data_string = self.rfile.read(int(self.headers["Content-Length"]))
                 msg = json.loads(data_string)
-                flag_dir = os.path.join(directory_to_serve, FLAGGING_DIRECTORY)
-                os.makedirs(flag_dir, exist_ok=True)
-                output = {'input': interface.input_interface.rebuild_flagged(flag_dir, msg),
-                          'output': interface.output_interface.rebuild_flagged(flag_dir, msg),
+                flag_dir = os.path.join(FLAGGING_DIRECTORY, str(interface.hash))
+                os.makedirs(FLAGGING_DIRECTORY, exist_ok=True)
+                output = {'input': interface.input_interface.rebuild_flagged(flag_dir, msg['data']['input_data']),
+                          'output': interface.output_interface.rebuild_flagged(flag_dir, msg['data']['output_data']),
                           'message': msg['data']['message']}
                 with open(os.path.join(flag_dir, FLAGGING_FILENAME), 'a+') as f:
                     f.write(json.dumps(output))

gradio/outputs.py

@@ -123,8 +123,7 @@ class Label(AbstractOutput):
         """
         Default rebuild method for label
         """
-        out = msg['data']['output']
-        return json.loads(out)
+        return json.loads(msg)
 
 
 class Textbox(AbstractOutput):
@@ -141,8 +140,7 @@ class Textbox(AbstractOutput):
         """
         Default rebuild method for label
         """
-        out = msg['data']['output']
-        return json.loads(out)
+        return json.loads(msg)
 
 
 class Image(AbstractOutput):
@@ -159,8 +157,7 @@ class Image(AbstractOutput):
         """
         Default rebuild method to decode a base64 image
         """
-        out = msg['data']['output']
-        im = preprocessing_utils.decode_base64_to_image(out)
+        im = preprocessing_utils.decode_base64_to_image(msg)
         timestamp = datetime.datetime.now()
         filename = f'output_{timestamp.strftime("%Y-%m-%d-%H-%M-%S")}.png'
         im.save(f'{dir}/{filename}', 'PNG')

static/flagged/1937261912/data.txt

@@ -0,0 +1 @@
+{"input": "input_1564123002454.png", "output": {"label": 0, "confidences": [{"label": 0, "confidence": 0.6294623613357544}, {"label": 9, "confidence": 0.20205073058605194}, {"label": 8, "confidence": 0.1176086813211441}]}}

static/flagged/560356067/data.txt

@@ -0,0 +1,2 @@
+{"input": "input_1564122648517.png", "output": {"label": 7, "confidences": [{"label": 7, "confidence": 0.9945800304412842}, {"label": 2, "confidence": 0.004080282989889383}, {"label": 0, "confidence": 0.0005652490654028952}]}}
+{"input": "input_1564122787604.png", "output": {"label": 6, "confidences": [{"label": 6, "confidence": 0.18893034756183624}, {"label": 0, "confidence": 0.1815452128648758}, {"label": 5, "confidence": 0.12178582698106766}]}}

static/flagged/data.txt

@@ -0,0 +1,3 @@
+{"input": "input_1564121741675.png", "output": {"label": 3, "confidences": [{"label": 3, "confidence": 0.49897417426109314}, {"label": 2, "confidence": 0.49327075481414795}, {"label": 9, "confidence": 0.0031273311469703913}]}, "message": ""}
+{"input": "input_1564122304245.png", "output": {"label": 1, "confidences": [{"label": 1, "confidence": 0.9119029641151428}, {"label": 0, "confidence": 0.04364873468875885}, {"label": 6, "confidence": 0.014955705031752586}]}}
+{"input": "input_1564122365828.png", "output": {"label": 1, "confidences": [{"label": 1, "confidence": 0.8408133387565613}, {"label": 4, "confidence": 0.07017231732606888}, {"label": 2, "confidence": 0.032813962548971176}]}}