process data files

enhancer/utils/fileprocessor.py

@@ -0,0 +1,96 @@
+import glob
+import os
+import numpy as np
+from scipy.io import wavfile
+
+class Fileprocessor:
+
+    def __init__(
+        self,
+        clean_dir,
+        noisy_dir,
+        sr = 16000,
+        matching_function = None
+    ):
+        self.clean_dir = clean_dir
+        self.noisy_dir = noisy_dir
+        self.sr = sr
+        self.matching_function = matching_function
+
+    @classmethod
+    def from_name(cls,
+                name:str,
+                clean_dir,
+                noisy_dir,
+                sr,
+                matching_function=None
+        ):
+
+        if name.lower() == "vctk":
+            return cls(clean_dir,noisy_dir,sr, Fileprocessor.match_vtck)
+        elif name.lower() == "dns-2020":
+            return cls(clean_dir,noisy_dir,sr, Fileprocessor.match_dns2020)
+        else:
+            return cls(clean_dir,noisy_dir,sr, matching_function)
+
+    def prepare_matching_dict(self):
+
+        if self.matching_function is None:
+            raise ValueError("Not a valid matching function")
+
+        return self.matching_function(self.clean_dir,self.noisy_dir,self.sr)
+
+    @staticmethod
+    def match_vtck(clean_path,noisy_path,sr):
+
+        matching_wavfiles = dict()
+        clean_filenames = [file.split('/')[-1] for file in glob.glob(os.path.join(clean_path,"*.wav"))]
+        noisy_filenames = [file.split('/')[-1] for file in glob.glob(os.path.join(noisy_path,"*.wav"))]
+        common_filenames = np.intersect1d(noisy_filenames,clean_filenames)
+
+        for file_name in common_filenames:
+
+             sr_clean, clean_file = wavfile.read(os.path.join(clean_path,file_name))
+             sr_noisy, noisy_file = wavfile.read(os.path.join(noisy_path,file_name))
+             if ((clean_file.shape[-1]==noisy_file.shape[-1]) and 
+                    (sr_clean==sr) and 
+                        (sr_noisy==sr)):
+                matching_wavfiles.update(
+                                    {os.path.join(clean_path,file_name):{"noisy":os.path.join(noisy_path,file_name),
+                                    "duration":clean_file.shape[-1]/sr}
+                                    }
+                                    )
+        return matching_wavfiles
+
+    @staticmethod
+    def match_dns2020(clean_path,noisy_path,sr):
+        
+        matching_wavfiles = dict()
+        clean_filenames = [file.split('/')[-1] for file in glob.glob(os.path.join(clean_path,"*.wav"))]
+        for clean_file in clean_filenames:
+            noisy_filenames = glob.glob(os.path.join(noisy_path,f"*_{clean_file}.wav"))
+            for noisy_file in noisy_filenames:
+
+                sr_clean, clean_file = wavfile.read(os.path.join(clean_path,clean_file))
+                sr_noisy, noisy_file = wavfile.read(noisy_file)
+                if ((clean_file.shape[-1]==noisy_file.shape[-1]) and 
+                        (sr_clean==sr) and 
+                            (sr_noisy==sr)):
+                    matching_wavfiles.update(
+                                        {os.path.join(clean_path,clean_file):{"noisy":noisy_file,
+                                        "duration":clean_file.shape[-1]/sr}
+                                        }
+                                        )
+
+        return matching_wavfiles
+
+
+
+
+        
+        
+
+
+        
+
+