{"id":28732941,"url":"https://github.com/estaheri7/signal_final_project","last_synced_at":"2026-07-17T15:31:26.759Z","repository":{"id":298296370,"uuid":"996230987","full_name":"Estaheri7/Signal_Final_Project","owner":"Estaheri7","description":"This application allows users to visualize the spectrogram and waveform of various synthetic and real audio signals as the final project for Signals \u0026 Systems course at Amirkabir University.","archived":false,"fork":false,"pushed_at":"2025-06-10T12:02:20.000Z","size":1331,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-30T22:30:41.149Z","etag":null,"topics":["signal-processing","spectrogram"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Estaheri7.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-06-04T16:39:43.000Z","updated_at":"2025-06-27T11:04:50.000Z","dependencies_parsed_at":null,"dependency_job_id":"7733d94f-25a8-490a-a0b7-5534e9d4abc9","html_url":"https://github.com/Estaheri7/Signal_Final_Project","commit_stats":null,"previous_names":["estaheri7/signal_final_project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Estaheri7/Signal_Final_Project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Estaheri7%2FSignal_Final_Project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Estaheri7%2FSignal_Final_Project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Estaheri7%2FSignal_Final_Project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Estaheri7%2FSignal_Final_Project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Estaheri7","download_url":"https://codeload.github.com/Estaheri7/Signal_Final_Project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Estaheri7%2FSignal_Final_Project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35587132,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-17T02:00:06.162Z","response_time":116,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["signal-processing","spectrogram"],"created_at":"2025-06-15T21:44:33.419Z","updated_at":"2026-07-17T15:31:26.753Z","avatar_url":"https://github.com/Estaheri7.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Spectrogram Viewer GUI 🎵📊\n\nThis is a Python-based GUI application that allows users to visualize the **spectrogram** and **waveform** of various synthetic and real audio signals. The app is built using `Tkinter` for the GUI and `matplotlib` for visualizations. It also uses `scipy`, `numpy`, and `sounddevice` for signal processing and playback.\n\n## 🚀 Features\n\n- Select from various synthetic signals:\n  - Linear Chirp\n  - Exponential Chirp\n  - Piecewise Sinusoid\n  - Piecewise Sum of Sinusoids\n- Load and analyze `.wav` audio files.\n- Visualize **spectrogram** with adjustable parameters:\n  - Window length\n  - Overlap\n  - Window type (Rectangular, Hamming, Hann)\n- View waveform of loaded audio files.\n- Play loaded audio using system sound.\n- Detect high-energy regions in audio based on energy threshold.\n\n## 🖼️ Screenshots\n\n1. **Main GUI window**\n   ![Main GUI](ScreenShots/spectrogram_app.jpg)\n2. **Spectrogram of a Linear Chirp**\n   ![Exponential Chrip](ScreenShots/exponential_chrip.jpg)\n3. **Waveform \u0026 Spectrogram view of an audio file**\n   ![Audio Time Domain](ScreenShots/audio_time_domain.jpg)\n   ![Audio Spectrogram](ScreenShots/audio_spectrogram.jpg)\n\n## 🛠️ Installation\n\n### 1. Clone the Repository\n\n```bash\ngit clone https://github.com/Estaheri7/Signal_Final_Project\ncd spectrogram-viewer\n```\n\n### 2. Install Dependencies\n\nMake sure you have Python 3.8+ installed.\n\n```bash\npip install numpy matplotlib scipy sounddevice\n```\n\nIf you're using `tkinter` for the first time, it’s usually preinstalled with Python. If not:\n\n- On Ubuntu/Debian:\n  ```bash\n  sudo apt-get install python3-tk\n  ```\n- On macOS:\n  Tkinter should be included with the Python installer from [python.org](https://www.python.org/).\n\n### 3. Run the App\n\n```bash\npython main.py\n```\n\n## 📁 Project Structure\n\n```bash\n.\n├── app.py              # GUI logic and signal visualization\n├── signals.py          # Synthetic signal generators\n├── main.py             # App launcher\n└── README.md           # You're here!\n```\n\n## 🎧 Usage Instructions\n\n1. **Choose a Signal Type** from the dropdown.\n2. **Set Parameters**:\n   - Window Length (e.g., 256)\n   - Overlap (e.g., 128)\n   - Window Type (hann, hamming, rectangular)\n3. **Click 'Plot Spectrogram'** to generate the frequency-time plot.\n4. To work with real audio:\n   - Click **Load Audio File**\n   - View **Waveform**\n   - Click **Play Audio**\n   - Use **Detect High-Energy Region** to analyze loud sections.\n\n## 📌 Notes\n\n- Audio files must be `.wav` format.\n- Stereo audio files will be downmixed to mono (first channel only).\n- Energy thresholding in high-energy detection is based on 60% of the peak window energy.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Festaheri7%2Fsignal_final_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Festaheri7%2Fsignal_final_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Festaheri7%2Fsignal_final_project/lists"}