From b8b02b65da8e08e0bcc63664e7bdfd643b695914 Mon Sep 17 00:00:00 2001
From: Abubakar Abid <a12d@stanford.edu>
Date: Wed, 19 Jan 2022 10:40:28 -0600
Subject: [PATCH] added code for previewing audio

---
 gradio/flagging.py | 28 ++++++++++++++++++++++++++--
 1 file changed, 26 insertions(+), 2 deletions(-)

diff --git a/gradio/flagging.py b/gradio/flagging.py
index a71b32e2c8..f13d1ff2ed 100644
--- a/gradio/flagging.py
+++ b/gradio/flagging.py
@@ -3,6 +3,7 @@ from abc import ABC, abstractmethod
 import csv
 import datetime
 import io
+import json
 import os
 from typing import Callable, Any, List, Optional, Tuple, TYPE_CHECKING
 
@@ -245,6 +246,7 @@ class HuggingFaceDatasetSaver(FlaggingCallback):
         path_to_dataset_repo = huggingface_hub.create_repo(
             name=self.dataset_name, token=self.hf_foken, 
             private=self.dataset_private, repo_type="dataset", exist_ok=True)
+        self.path_to_dataset_repo = path_to_dataset_repo  # e.g. "https://huggingface.co/datasets/abidlabs/test-audio-10"
         self.flagging_dir = flagging_dir
         self.dataset_dir = os.path.join(flagging_dir, self.dataset_name)
         self.repo = huggingface_hub.Repository(
@@ -254,6 +256,7 @@ class HuggingFaceDatasetSaver(FlaggingCallback):
         
         #Should filename be user-specified?
         self.log_file = os.path.join(self.dataset_dir, "data.csv")  
+        self.infos_file = os.path.join(self.dataset_dir, "dataset_infos.json")  
 
     def flag(
         self, 
@@ -265,20 +268,34 @@ class HuggingFaceDatasetSaver(FlaggingCallback):
         username: Optional[str] = None
     ) -> int:        
         is_new = not os.path.exists(self.log_file)
+        infos = {"flagged": {"features": {}}}
         
         with open(self.log_file, "a", newline="") as csvfile:
             writer = csv.writer(csvfile)
             
             # File previews for certain input and output types
-            file_preview_types = (gr.inputs.Audio, gr.outputs.Audio)
+            file_preview_types = {
+                gr.inputs.Audio: "Audio", 
+                gr.outputs.Audio: "Audio"
+            }
             
             # Generate the headers
             if is_new:
                 headers = []
                 for component in interface.input_components + interface.output_components:
                     headers.append(component.label)
+                    infos["flagged"]["features"][component.label] = {
+                        "dtype": "string", 
+                        "_type": "Value"
+                    }
                     if isinstance(component, file_preview_types):
                         headers.append(interface.label + " file")
+                        for _component, _type in file_preview_types.items():
+                            if isinstance(component, _component):
+                                infos["flagged"]["features"][component.label] = {
+                                    "_type": _type                                    
+                                }
+                            break
                 if interface.flagging_options is not None:
                     headers.append("flag")
                 writer.writerow(headers)
@@ -289,16 +306,23 @@ class HuggingFaceDatasetSaver(FlaggingCallback):
                 filepath = input.save_flagged(self.dataset_dir, input.label, input_data[i], None)
                 csv_data.append(filepath)
                 if isinstance(component, file_preview_types):
-                    csv_data.append("https://huggingface.co/datasets/abidlabs/test-audio-1/resolve/main/x/0.wav")
+                    csv_data.append("{}/resolve/main/{}".format(
+                        self.path_to_dataset_repo, filepath))
             for i, output in enumerate(interface.output_components):
                 csv_data.append(output.save_flagged(self.dataset_dir, interface.config["output_components"][i]["label"], output_data[i], None) if
                     output_data[i] is not None else "")
+                if isinstance(component, file_preview_types):
+                    csv_data.append("{}/resolve/main/{}".format(
+                        self.path_to_dataset_repo, filepath))
             if flag_option is not None:
                 csv_data.append(flag_option)
             
             # Write the rows
             writer.writerow(csv_data)
 
+        if is_new:
+            json.dump(infos, open(self.infos_file, "w"))
+            
         # return number of samples in dataset
         with open(self.log_file, "r") as csvfile:
             line_count = len([None for row in csv.reader(csvfile)]) - 1