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Iván Eduardo Chavez Ayub
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## Version 4.1
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**Release date:** 1 August 2025
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### Model Enhancement and Utilization
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#### 1.1 **Enhanced GPU Utilization and Error Handling**
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- **Robust Provider Configuration**: Added a private method `_select_providers` to intelligently select ONNX runtime providers based on the chosen GPU and improve model execution efficiency.
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- **Dynamic Fall-back Mechanism**: Enhanced `_load_inferenceSession` to prioritize loading models on GPU providers and gracefully fallback to CPU providers if GPU initialization fails, coupled with detailed logging.
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- **Improved Model Initialization**: Ensured comprehensive validation and error handling during model loading to enhance stability across various hardware environments.
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### Compatibility and Runtime Improvements
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#### 2.1 **Addressed NumPy and OpenCV Compatibility**
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- **Resolved Import Errors**: Fixed critical compatibility issues between NumPy 2.x and OpenCV by downgrading to NumPy 1.26.4, preventing `_ARRAY_API not found` and `numpy.core.multiarray failed to import` errors.
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- **Critical Module Validation**: Ensured that all critical libraries (OpenCV, ONNX Runtime, CustomTkinter) load successfully without compatibility warnings, enhancing overall application reliability.
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- **Runtime Environment Stability**: Resolved module loading conflicts that previously caused application crashes during startup.
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### Performance Optimization
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#### 3.1 **Memory and Resource Management**
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- **Contiguous Memory Utilization**: Enhanced use of `numpy.ascontiguousarray` throughout image processing pipelines to optimize memory usage during intensive AI processing tasks.
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- **GPU Memory Error Recovery**: Improved handling of GPU memory allocation failures with automatic fallback to CPU processing when DirectML providers are unavailable.
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- **Processing Pipeline Optimization**: Streamlined AI model loading and inference execution for better resource utilization across different hardware configurations.
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### Code Quality and Error Handling
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#### 4.1 **Enhanced Error Resilience**
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- **Syntax Error Resolution**: Fixed critical syntax error in `_load_inferenceSession` method that prevented proper AI model initialization.
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- **Improved Error Messaging**: Enhanced logging capabilities with more informative error messages and warnings for better user diagnostics and troubleshooting.
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- **Graceful Degradation**: Implemented improved fallback strategies for GPU resource issues, effectively preventing application crashes by dynamically adjusting processing pathways.
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- **Provider Validation**: Added comprehensive validation for ONNX runtime providers with automatic fallback from GPU to CPU execution when hardware acceleration is unavailable.
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### UI and User Experience
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#### 5.1 **Application Stability and Feedback**
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- **Startup Reliability**: Resolved critical startup issues that prevented the application from launching due to module compatibility problems.
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- **Processing Status Updates**: Enhanced real-time feedback during AI model loading and image/video processing operations.
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- **Error Notification**: Improved error dialogs and status messages to provide clearer information about processing states and potential issues.
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- **Hardware Compatibility**: Better detection and handling of different GPU configurations, with informative warnings when falling back to CPU processing.
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### Technical Improvements
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#### 6.1 **Model Loading Architecture**
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- **Modular Provider Selection**: Separated provider selection logic into dedicated methods for better code organization and maintainability.
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- **Robust Model Validation**: Enhanced file existence checking and model integrity validation before attempting to load AI models.
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- **Cross-Platform Compatibility**: Improved compatibility across different Windows configurations and GPU setups.
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---
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## Version 4.0.1
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**Release date:** 27 July 2025
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@@ -163,8 +219,6 @@
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- The application now explicitly handles images with an alpha channel (4-channel BGRA) when using face restoration models. A new import for `COLOR_BGRA2BGR` was added, and it is used within `preprocess_face_image` to convert images to the 3-channel BGR format expected by the GFPGAN model. This prevents runtime errors and ensures correct processing of PNGs or other images with transparency.
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---
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## Version 2.2
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**Release date:** 7 July 2025
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@@ -242,8 +296,6 @@
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- Core methods in AI classes now include checks for `None` inputs and feature default fallbacks (`case _:`) in `match` statements to prevent unexpected errors with unsupported data.
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--
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## Version 2.1
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**Release date:** 23 June 2025
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@@ -2,12 +2,12 @@
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<div align="center">
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# Warlock-Studio
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# 🎭 Warlock-Studio
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### _AI Media Enhancement Suite_
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[](https://github.com/Ivan-Ayub97/Warlock-Studio/releases)
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[](https://github.com/Ivan-Ayub97/Warlock-Studio/releases/tag/4.0.1)
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[](https://github.com/Ivan-Ayub97/Warlock-Studio/releases/tag/4.1)
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[](LICENSE)
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[](https://github.com/Ivan-Ayub97/Warlock-Studio/releases)
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@@ -19,13 +19,13 @@ _Transform your media with cutting-edge AI technology_
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**Warlock-Studio** is a powerful, open-source desktop application for Windows that integrates state-of-the-art AI models for video and image enhancement. Inspired by the work of [Djdefrag](https://github.com/Djdefrag) on tools like **QualityScaler** and **FluidFrames**, this suite provides a unified, high-performance interface for upscaling, restoration, and frame interpolation.
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Version 4.0.1 continues this evolution with enhanced AI architecture and improved code stability for even better performance and reliability. Note: The SuperResolution-10 model has been removed in this version for better performance optimization.
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Version 4.1 builds on previous improvements with enhanced GPU utilization, comprehensive compatibility fixes, and optimization of model loading processes to provide a robust, reliable, and high-performance AI media enhancement experience.
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---
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### ► Download Installer (v4.0.1)
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### ► Download Installer (v4.1) - Now Even Better
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**NEW**: Installer size reduced from **1.4GB to ~450MB**! AI models (400MB) are automatically downloaded when first launched.
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🚀 **NEW**: Installer size reduced from **1.4GB to ~450MB**! AI models (400MB) are automatically downloaded when first launched.
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Get the latest stable release from any of the following platforms:
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@@ -37,7 +37,7 @@ Get the latest stable release from any of the following platforms:
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</a>
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</td>
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<td align="center" width="33%">
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<a href="https://github.com/Ivan-Ayub97/Warlock-Studio/releases/download/4.0.1/Warlock-Studio4.0.1Setup.zip">
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<a href="https://github.com/Ivan-Ayub97/Warlock-Studio/releases/download/4.1/Warlock-Studio4.1Setup.zip">
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<img src="rsc/GitHub_Lockup_Light.png" alt="Download from GitHub" width="200" />
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</a>
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</td>
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@@ -74,29 +74,31 @@ Get the latest stable release from any of the following platforms:
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---
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## What's New in Version 4.0.1
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## What's New in Version 4.1
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- **Model Optimization:** Removed SuperResolution-10 model to improve overall performance and reduce complexity. For extreme upscaling needs, we recommend using Real-ESRGAN or BSRGAN models which provide excellent results.
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- 🔧 **Model Optimization:** Removed SuperResolution-10 model to improve overall performance and reduce complexity. For extreme upscaling needs, we recommend using Real-ESRGAN or BSRGAN models which provide excellent results.
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- ✅ **Enhanced AI Architecture:** Implemented robust ONNX model loading, GPU acceleration support, and comprehensive error handling.
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- ✅ **Code Quality Improvements:** Fixed critical import errors, consolidated duplicate code sections, and improved type annotations for better maintainability.
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- ✅ **Improved Error Handling:** Added graceful degradation mechanisms that prevent crashes and provide meaningful error messages during processing.
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- ✅ **Streamlined Model Integration:** Optimized model integration in the UI and processing pipeline for better performance.
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- 🚀 **Smart Model Distribution:** Lightweight installer (~450MB) with automatic AI model download system that fetches models on first launch.
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- 📦 **Optimized Packaging:** Enhanced PyInstaller configuration excludes AI models from executable, significantly reducing download and installation time.
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- 🟢 **Enhanced GPU Utilization**: Improved provider selection logic for better model execution efficiency across different hardware configurations.
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- 🚀 **Compatibility Fixes**: Addressed critical module compatibility by ensuring consistent runtime environment for NumPy and OpenCV libraries.
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- 📦 **Performance and Stability**: Refined memory and resource management, with enhanced error messaging and fallback strategies to ensure robust application performance under varying conditions.
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- ✅ **User Experience Enhancements**: Improved startup reliability and user notifications for smooth interaction and feedback.
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---
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## Smart Model Distribution System
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## 🌐 Smart Model Distribution System
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Version 4.0 introduces a revolutionary approach to AI model distribution:
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### **Lightweight Installation**
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### 🎯 **Lightweight Installation**
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- **Installer Size:** Reduced from 1.4GB to ~450MB (68% size reduction)
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- **First Launch:** AI models (~400MB) download automatically with progress tracking
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- **Bandwidth Friendly:** Users with limited internet can get started faster
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### **Reliability Features**
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### 🛡️ **Reliability Features**
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- **Integrity Validation:** Downloaded models are verified for completeness
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- **Graceful Degradation:** Application provides clear feedback if models aren't available
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@@ -106,7 +108,7 @@ Version 4.0 introduces a revolutionary approach to AI model distribution:
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## Interface Previews
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### 🔹 Main View (v4.0.1)
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### 🔹 Main View (v4.1)
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@@ -153,9 +155,11 @@ Warlock-Studio uses [PyInstaller](https://www.pyinstaller.org/) and [Inno Setup]
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### Installation Window Previews
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---
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@@ -168,7 +172,7 @@ Warlock-Studio uses [PyInstaller](https://www.pyinstaller.org/) and [Inno Setup]
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---
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## Development Status — v4.0.1-07.25
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## Development Status — v4.1-08.01
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| Component | Status | Notes |
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| :---------------------------------- | :-------------- | :----------------------------------------------------------------------------------- |
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@@ -202,7 +206,6 @@ Warlock-Studio/
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├──RealSRx4_Anime_fp16.onnx
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├──RIFE_fp32.onnx
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├──RIFE_Lite_fp32.onnx
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│
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├──Assets/
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│
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└──├──banner.png
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@@ -216,16 +219,22 @@ Warlock-Studio/
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├──upscale_icon.png
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├──wizard-image.bmp
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└──wizard-small.bmp
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│
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├──rsc/
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│
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└──├──png files used in repo...
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│
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└──├──badge-color.png
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├──Capture.png
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├──CaptureRIFE.png
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├──google_drive-logo.png
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├──WorkflowBSRGAN.png
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├──WorkflowIRCNN.png
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├──WorkflowRealESRGAN.png
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├──WorkflowRIFE.png
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└──Installation_window2.png
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├──Manual/
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│
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└──├──v4.0.1_User_Manual_EN.pdf
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└──├──Manual_EN.pdf
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├──Manual_EN.tex
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├──v4.0.1_User_Manual_ES.pdf
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├──Manual_ES.pdf
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└──Manual_ES.tex
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│
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├──CHANGELOG.md
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@@ -237,6 +246,8 @@ Warlock-Studio/
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├──README.md # This File
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├──SECURITY.md
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├──Setup.iss
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├──Manual_ES.pdf
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├──Manual_EN.pdf
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├──Warlock-Studio.py # Main
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└──Warlock-Studio.spec
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```
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; ===================================================================
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#define AppName "Warlock-Studio"
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#define AppVersion "4.0.1"
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#define AppVersion "4.1"
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#define AppPublisher "Iván Eduardo Chavez Ayub"
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#define AppURL "https://github.com/Ivan-Ayub97/Warlock-Studio"
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#define AppExeName "Warlock-Studio.exe"
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