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I configured the AEM-Adobe Target integration by enabling:

• IMS configuration for authentication
• Legacy Adobe Target Cloud Config and New Adobe Target Cloud Config
• Default workspace assignment in Adobe Developer Console Project
• Approver permissions for the API credential in the Admin Console

However, when attempting to create an A/B test or Experience Targeting (XT) activity from AEM and sync it to Adobe Target, the Target Configuration dropdown was empty, indicating that no configurations were detected.

Root Cause & Resolution

Upon further analysis, I identified that the issue was due to the user not being part of the target-activity-authors group. After adding the user to this group, the activity creation process began recognizing all available Adobe Target configurations, including both legacy and new configurations.

Now, activities can be successfully created and synced to the default workspace once the experience is defined.

When we try to create A/B Testing or Experience Targeting activities from the AEM Activities Console and sync them to Adobe Target

The synchronization fails with the following error, and the status is shown as 'Not Synced'.

The root cause of the issue is that no experience variations were defined for the activity. We created different experiences but did not apply any pages to the activity or enable the required experience changes. To resolve the issue, select the page where this activity should be enabled and target the required components and assign the changes for appropriate experiences. This should allow the activity to sync successfully with Adobe Target.

Introduction

Music generation with Python has become more accessible with powerful libraries that allow us to compose melodies, generate MIDI files, and convert them into audio formats like WAV and MP3. This guide walks through the process of creating a MIDI file, synthesizing it into WAV using FluidSynth, and finally converting it to MP3 using pydub.

By the end of this guide, you will have a fully functional Python script that generates music and exports it as an MP3 file.

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Why Use Python for Music Generation?

Python provides several libraries that make it easy to create and manipulate music:

• MIDIUtil – Generates MIDI files programmatically.
• Mingus – Provides music theory functions and chord generation.
• FluidSynth – A real-time synthesizer that converts MIDI to WAV.
• pydub – Converts audio formats, such as WAV to MP3.

Using these libraries, we can generate music from scratch and export it into an audio format that can be played on any device.

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Setting Up the Environment

Before running the script, install the necessary dependencies:

Install Python Libraries

Run the following command in your terminal:

pip install midiutil mingus pyfluidsynth pydub

Install FluidSynth

1. Download FluidSynth from the official repository:
   FluidSynth Releases
2. Extract it to C:\tools\fluidsynth
3. Add C:\tools\fluidsynth\bin to your system PATH (for command-line access).
4. Verify the installation by running:

   fluidsynth --version

Download a SoundFont (.sf2) File

FluidSynth requires a SoundFont file to map MIDI notes to instrument sounds.

• Download FluidR3_GM.sf2:
  FluidR3_GM SoundFont from member.keymusician.com/Member/FluidR3_GM/index.html
• Move it to the same folder as your Python script or any preferred directory.

How Music is Generated in Python

Music generation in Python follows these key principles:

Understanding MIDI File Structure

A MIDI (Musical Instrument Digital Interface) file contains:

• Note Data – The pitches and durations of notes.
• Velocity – The intensity of each note.
• Instrument Information – Which instruments to use for playback.

Unlike audio formats like MP3 or WAV, MIDI does not contain actual sound data, meaning it must be played back using a synthesizer like FluidSynth.

Breaking Down the Composition Process

1. Chords and Progressions

   • Chords are groups of notes played together.
   • A chord progression is a sequence of chords that forms a harmonic structure for the music.
   • Example: "C → G → Am → F" is a common progression.

2. Melody Generation

   • A melody is a sequence of individual notes that create a recognizable tune.
   • The script selects notes from a chord to create a simple melodic line.

3. Bassline Generation

   • The bassline is usually the root note of each chord, played in a lower octave.
   • It provides rhythm and harmonic stability.

4. MIDI to Audio Conversion

   • Since MIDI files do not contain actual sound, FluidSynth uses a SoundFont to generate audio.
   • Finally, we convert the generated WAV file to MP3 using pydub.

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Python Script to Generate MIDI and Convert to MP3

This script will:

1. Generate a MIDI file with chord progressions, a melody, and a bassline.
2. Convert MIDI to WAV using FluidSynth and a SoundFont.
3. Convert WAV to MP3 using pydub.

Python Script

import random
import os
import subprocess
from midiutil import MIDIFile
from mingus.core import chords
from pydub import AudioSegment

# Define paths
SOUNDFONT_PATH =os.path.join(os.getcwd(), "FluidR3_GM.sf2")  # Update your SoundFont path
MIDI_FILENAME = "generated_music.mid"
WAV_FILENAME = "generated_music.wav"
MP3_FILENAME = "generated_music.mp3"

# Define chord progressions
verse = ["C", "G", "Am", "F"]
chorus = ["F", "C", "G", "Am"]
bridge = ["Dm", "A7", "G", "C"]
song_structure = [verse, verse, chorus, verse, bridge, chorus]

# MIDI settings
track = 0
channel = 0
time = 0  # Start time in beats
tempo = 120  # BPM
volume = 100  # MIDI velocity

# Create a MIDI file
MyMIDI = MIDIFile(1)
MyMIDI.addTempo(track, time, tempo)

# Assign instruments
instrument_chords = 0  # Acoustic Piano
instrument_melody = 40  # Violin
instrument_bass = 33  # Acoustic Bass

MyMIDI.addProgramChange(track, channel, time, instrument_chords)
MyMIDI.addProgramChange(track, channel + 1, time, instrument_melody)
MyMIDI.addProgramChange(track, channel + 2, time, instrument_bass)

# Convert note names to MIDI numbers
def note_to_number(note: str, octave: int) -> int:
    NOTES = ['C', 'C#', 'D', 'Eb', 'E', 'F', 'F#', 'G', 'Ab', 'A', 'Bb', 'B']
    NOTES_IN_OCTAVE = len(NOTES)
    return NOTES.index(note) + (NOTES_IN_OCTAVE * octave)

# Generate music
for section in song_structure:
    for chord in section:
        chord_notes = chords.from_shorthand(chord)
        random.shuffle(chord_notes)
        rhythm_pattern = [0, 0.5, 1, 1.5, 2, 2.5, 3]

        # Add chords
        for i, note in enumerate(chord_notes):
            octave = 3
            midi_note = note_to_number(note, octave)
            MyMIDI.addNote(track, channel, midi_note, time + rhythm_pattern[i % len(rhythm_pattern)], 1, volume)

        # Add bassline
        bass_note = note_to_number(chord_notes[0], 2)
        MyMIDI.addNote(track, channel + 2, bass_note, time, 4, volume)

        # Add melody
        melody_note = note_to_number(random.choice(chord_notes), 5)
        melody_duration = random.choice([0.5, 1, 1.5])
        MyMIDI.addNote(track, channel + 1, melody_note, time + 2, melody_duration, volume)

        time += 4

# Save MIDI file
with open(MIDI_FILENAME, "wb") as output_file:
    MyMIDI.writeFile(output_file)

# Convert MIDI to WAV using FluidSynth
subprocess.run(f'fluidsynth -ni -F {WAV_FILENAME} -r 44100 {SOUNDFONT_PATH} {MIDI_FILENAME}', shell=True, check=True)

# Convert WAV to MP3 using pydub
AudioSegment.from_wav(WAV_FILENAME).export(MP3_FILENAME, format="mp3")

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Running the Script

Once dependencies are installed, run:

python generate_music.py

This generates:

• generated_music.mid (MIDI file)
• generated_music.wav (WAV file)
• generated_music.mp3 (MP3 file)

---

Next Steps

• Customize the chord progressions
• Experiment with different instruments
• Generate longer compositions
• Integrate AI-generated melodies

Start generating music with Python today!

Have you ever wanted to convert an MP3 file into a MIDI format for music production, transcription, or remixing?

BasicPitch by Spotify is an open-source AI-powered tool that makes this process simple and accurate.

With just a few lines of Python code, you can extract notes and melodies from an audio file and use them in a Digital Audio Workstation (DAW) or for further analysis. Let’s dive in.

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What is BasicPitch?

BasicPitch is an AI-powered polyphonic pitch detection model developed by Spotify. Unlike traditional MIDI conversion tools, BasicPitch:

• Detects multiple notes at once (polyphonic transcription)
• Understands pitch bends and vibrato
• Works with various instruments, not just piano
• Is lightweight and open-source

More about BasicPitch:

• Try it Online: BasicPitch Web Demo
• GitHub Repository: Spotify BasicPitch

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Steps to Convert MP3 to MIDI

1. Install Dependencies

First, install the required Python packages:

pip install basic-pitch ffmpeg-python

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2. Use This Python Script

This script will process the MP3 file, run BasicPitch’s AI model, and save the MIDI file.

import os
from basic_pitch.inference import predict_and_save
from basic_pitch import ICASSP_2022_MODEL_PATH

# --------------------------------------
# MP3 to MIDI Conversion using BasicPitch by Spotify
# This script processes an MP3 file using BasicPitch 
# and saves the resulting MIDI file in the output directory.
# --------------------------------------

# Define the input MP3 file path (Replace "song.mp3" with your actual file)
input_mp3 = r"song.mp3"  # Ensure the file is in the same directory or provide a full path

# Define the output directory where MIDI files will be saved
output_dir = r"output"

# Check if the input MP3 file exists before proceeding
if not os.path.exists(input_mp3):
    raise FileNotFoundError(f"Error: The file '{input_mp3}' does not exist. Please check the path.")

# Load the BasicPitch model
basic_pitch_model = str(ICASSP_2022_MODEL_PATH)

# --------------------------------------
# Running the BasicPitch Inference Model
# The model will analyze the MP3 file and generate a MIDI file.
# --------------------------------------

print("Running BasicPitch inference on the MP3 file...")
predict_and_save(
    [input_mp3],  # Use MP3 directly, no need to convert to WAV manually
    output_dir,   # Save MIDI files in the output directory
    save_midi=True,  # Enable saving the MIDI output
    sonify_midi=False,  # Disable MIDI sonification (audio rendering)
    save_model_outputs=False,  # Disable saving raw model outputs
    save_notes=False,  # Disable saving individual note files
    model_or_model_path=basic_pitch_model,  # Load BasicPitch model
)

# MIDI conversion complete. Check the output folder.
print(f"Conversion complete. Check the '{output_dir}' folder for the MIDI files.")

---

Setup Instructions

Why Use BasicPitch Instead of Other MIDI Conversion Tools?

Feature	BasicPitch (Spotify)	Other Tools
AI-powered	Yes	Mostly rule-based
Polyphonic (Multiple Notes)	Yes	Mostly monophonic
Pitch Bends and Vibrato	Yes	No or limited
Open Source	Yes	Often paid
Lightweight and Fast	Yes	Some require heavy processing

---

Real-World Use Cases

• Convert guitar recordings to MIDI for editing in DAWs like Ableton and FL Studio
• Transcribe piano melodies into MIDI for remixing or re-orchestrating
• Turn vocal hums into music notes to create melodies from scratch
• Use for music education and research to analyze complex musical pieces

---

What’s Next?

Once your MP3 is converted to MIDI, you can:

• Import it into DAWs like Ableton, FL Studio, Logic Pro, or GarageBand
• Assign virtual instruments to the MIDI notes and create new sounds
• Use it for sheet music transcription and study compositions

Have you tried BasicPitch yet? What are your thoughts? Let me know in the comments.

---

Useful Resources

• Spotify BasicPitch GitHub
• BasicPitch Online Demo
• Librosa Audio Processing

OWASP Dependency Check is a software composition analysis (SCA) tool that scans your project's dependencies for known vulnerabilities. It cross-references dependencies with databases like the National Vulnerability Database (NVD) to help you proactively identify and mitigate risks in third-party libraries. This guide explains how to integrate and use OWASP Dependency Check in a Maven project.

---

What is OWASP Dependency Check?

OWASP Dependency Check is an open-source tool that:

• Identifies vulnerabilities in project dependencies by referencing public vulnerability databases.
• Helps mitigate risks by providing CVE details, severity levels, and suggested fixes.
• Integrates seamlessly with Maven, Gradle, CI/CD pipelines, and other build tools.

---

Step 1: Add Dependency Check Plugin to Maven

To integrate Dependency Check with Maven, add the plugin configuration to your pom.xml:

<build>
    <plugins>
        <plugin>
            <groupId>org.owasp</groupId>
            <artifactId>dependency-check-maven</artifactId>
            <version>8.4.0</version> <!-- Use the latest version -->
            <executions>
                <execution>
                    <goals>
                        <goal>check</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
    </plugins>
</build>

---

Step 2: Run the Dependency Check

Execute the following Maven command to start the vulnerability scan:

mvn dependency-check:check

Use mvn dependency-check:update-only on subsequent runs to reduce execution time.

What Happens:

• The plugin scans your project's dependencies, fetches data from the NVD, and identifies vulnerabilities.
• Reports are generated in the target directory:
  • HTML Report: dependency-check-report.html
  • JSON Report: dependency-check-report.json

---

Step 3: Review the Results

1. Access the Reports:

   • Navigate to the target directory to view the generated reports.
   • Open dependency-check-report.html for a detailed summary.

2. Understand the Output:

   • Each dependency is checked for known CVEs.
   • Severity is indicated using the CVSS (Common Vulnerability Scoring System).

3. Take Action:

   • Update vulnerable dependencies to patched versions.
   • Exclude unused or unnecessary dependencies.

---

Step 4: Configure Dependency Check

Customize the plugin behavior to suit your project needs. Use the <configuration> tag in pom.xml for advanced settings.

Example Configuration:

<plugin>
    <groupId>org.owasp</groupId>
    <artifactId>dependency-check-maven</artifactId>
    <version>8.4.0</version>
    <configuration>
        <outputDirectory>./dependency-check-reports</outputDirectory>
        <formats>
            <format>HTML</format>
            <format>JSON</format>
        </formats>
        <failBuildOnCVSS>7</failBuildOnCVSS> <!-- Fail build for CVSS >= 7 -->
        <nvd.api.key>your-nvd-api-key</nvd.api.key> <!-- Optional NVD API Key -->
    </configuration>
</plugin>

---

Step 5: Enhance Performance with NVD API Key

The NVD API key helps:

• Improve scan reliability by increasing request limits to the NVD database.
• Reduce delays caused by throttling during frequent scans.

How to Use the API Key:

1. Obtain an API Key:
• Request it from NVD API Key Registration.
2. Configure the API Key:
   • Add it to your pom.xml:

     <configuration>
         <nvd.api.key>your-nvd-api-key</nvd.api.key>
     </configuration>
     

   • Or pass it via the command line:

     mvn dependency-check:check -Dnvd.api.key=your-nvd-api-key

   • Or set it as an environment variable:

     export NVD_API_KEY=your-nvd-api-key

---

Step 6: Automate with CI/CD

Integrate OWASP Dependency Check into your CI/CD pipeline to ensure continuous security validation.

GitHub Actions Example:

name: Dependency Check

on:
  push:
    branches:
      - main

jobs:
  dependency-check:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout Code
        uses: actions/checkout@v3
      - name: Set up Java
        uses: actions/setup-java@v3
        with:
          java-version: 11
      - name: OWASP Dependency Check
        run: mvn dependency-check:check

---

Common Issues and Solutions

1. Slow Scans:

   • Use an NVD API key for faster updates.
   • Run mvn dependency-check:update-only to pre-cache vulnerability data.

2. False Positives:

   • Exclude specific dependencies:

     <configuration>
         <excludes>
             <exclude>com.example:example-dependency</exclude>
         </excludes>
     </configuration>
     

3. Large Projects:

   • Adjust database refresh intervals:

     <cveValidForHours>72</cveValidForHours>

---

Tips for Best Practices

1. Update Regularly:
   • Ensure the plugin and NVD database are up-to-date.
2. Fail Builds on High-Risk Vulnerabilities:
   • Use <failBuildOnCVSS> to enforce a security threshold.
3. Exclude Dev-Only Dependencies:
   • Use <scope>test</scope> for test dependencies that don’t need production scans.

---

Conclusion

OWASP Dependency Check is a vital tool for identifying and mitigating risks in your project's dependencies. By integrating it into your Maven project and CI/CD pipelines, you can proactively manage vulnerabilities and ensure compliance with security standards.