initial commit

README.md

@@ -1,5 +1,5 @@
 ---
-title: Deep Filter
+title: Audio Enhancement with Deep Filter
 emoji: 📈
 colorFrom: blue
 colorTo: green

app.py

@@ -0,0 +1,120 @@
+import os
+import ffmpeg
+import uuid
+import streamlit as st
+import shutil
+import logging
+
+logging.basicConfig(level=logging.INFO)  # Set the logging level
+
+def log_info(message):
+    logging.info(message)
+
+def log_error(error_message):
+    logging.error(error_message)
+
+# Function to extract audio using ffmpeg
+def convert_audio(input_file):
+    audio_file = f"{input_file}.wav"
+    ffmpeg.input(input_file).output(audio_file, ar=48000, ac=1).run()
+    return audio_file
+
+# Function to split audio into segments
+def split_audio(audio_file):
+    segment_pattern = os.path.splitext(audio_file)[0] + ".segmented_%03d.wav"
+    ffmpeg.input(audio_file).output(segment_pattern, f="segment", segment_time=300).run()
+    return segment_pattern
+
+# Function to filter each audio segment
+def filter_audio(segments):
+    filtered_dir = "temp-out"
+    os.makedirs(filtered_dir, exist_ok=True)
+    os.system(f"deepFilter -a 20 -o {filtered_dir} {segments.replace('%03d.wav', '')}*.wav")
+    os.system(f"rm {segments.replace('%03d.wav', '')}*.wav")
+    return filtered_dir
+
+# Function to combine filtered segments using sox
+def combine_segments(filtered_dir, output_file):
+    os.system(f"sox {filtered_dir}/*.wav {output_file}")
+    return output_file
+
+# Function to check if input file is video
+def is_video(input_file):
+    result = os.popen(f"ffprobe -v error -show_entries stream=codec_type -of default=noprint_wrappers=1:nokey=1 {input_file}").read()
+    return "video" in result.lower()
+
+# Function to get format info for audio files
+def get_format_info(input_file):
+    result = os.popen(f"ffprobe -v error -show_entries stream=codec_name -of default=noprint_wrappers=1:nokey=1 {input_file}").read()
+    return result
+
+
+# Function to handle video or audio input
+def process_input(input_file):
+    try:
+        audio_file = convert_audio(input_file)
+        segments = split_audio(audio_file)
+        filtered_dir = filter_audio(segments)
+        output_file = combine_segments(filtered_dir, f"{input_file}.filtered.wav")
+        shutil.rmtree(filtered_dir)
+        output_format = input_file.split(".")[-1]
+
+        if is_video(input_file):
+            audio_aac_file = f"filtered-{input_file}.aac"
+            ffmpeg.input(output_file).output(audio_aac_file, ar=44100, codec="aac").run()
+
+            video_stream = ffmpeg.input(input_file).video
+            audio_aac_stream = ffmpeg.input(audio_aac_file).audio
+            
+            merged_file = f"filtered-{input_file}.{output_format}"
+            ffmpeg.output(video_stream, audio_aac_stream, merged_file, vcodec="copy", acodec="copy").run()
+
+            os.remove(audio_aac_file)
+            os.remove(output_file)
+            os.remove(audio_file)
+            os.rename(merged_file, input_file)
+
+            return input_file
+        else:
+            ffmpeg.input(output_file).output(f"filtered-{input_file}.{output_format}", ac=1, ar=16000).run()
+
+            os.rename(f"filtered-{input_file}.{output_format}", input_file)
+            os.remove(output_file)
+            os.remove(audio_file)
+
+            return input_file
+    except Exception as e:
+        log_error(f"Error occurred during processing: {str(e)}")
+        return None
+
+# Streamlit UI
+st.title("Audio Enhancement with Deep Filter")
+
+uploaded_file = st.file_uploader("Upload a file", type=["mp4", "wav", "mp3", "aac", "m4a", "flac", "ogg", "opus", "wma", "webm", "mkv"])
+
+if uploaded_file is not None:
+    try:
+        file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type, "FileSize": uploaded_file.size}
+        st.write(file_details)
+
+        if st.button("Process File"):
+            # generate a random file name to save the uploaded file
+            file_path = f"temp-{str(uuid.uuid4())[:8]}.{uploaded_file.name.split('.')[-1]}"
+
+            with open(file_path, "wb") as f:
+                f.write(uploaded_file.getbuffer())
+
+            output_file_path = process_input(file_path)
+
+            if output_file_path and os.path.exists(output_file_path):
+                data = open(output_file_path, "rb").read()
+                os.remove(file_path)
+
+                st.success("File processed successfully!")
+                st.download_button(label="Download Processed File", 
+                                    data=data,
+                                    file_name="filtered-" + uploaded_file.name)
+            else:
+                st.error("File processing failed.")
+    except Exception as e:
+        log_error(f"Error occurred during file processing: {str(e)}")

packages.txt

@@ -0,0 +1 @@
+sox

requirements.txt

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+torch
+torchaudio
+deepfilternet