Deep Learning Visual Integration captures chart screenshots and price data to send to an external server, where models like Random Forest or Generative Adversarial Imitation Learning process the visual information. The EA then receives and displays buy or sell signals returned by the model. It functions primarily as a data exporter and execution bridge, requiring a separate server-side environment to perform the actual machine learning predictions.
Socket-based communication with external servers
Automated chart screenshot capture for visual analysis
Read from Socket_For_Vision_Step1.mq4. Defaults are the author's; change them in the EA's Inputs tab.
Name
Type
Default
Description
server_port
ushort
5555
server_ip
string
127.0.0.1
MagicNumber
int
20190730
Slippage
int
2
How to Install It
1Download the sourceUse "Download source (.zip)" above, or clone RainBowT0506/MT4-Deep-Learning-Visual-Integration from GitHub, and unzip it.
2Open the data folderIn MetaTrader choose File, then Open Data Folder, and go to MQL4/Experts or MQL5/Experts.
3Copy the filesCopy the .mq4 / .mq5 file into Experts.
4Compile in MetaEditorOpen the file in MetaEditor and press Compile. Fix any missing includes the compiler reports.
5Test before you tradeRun it in the Strategy Tester, then attach it to a demo chart and allow algorithmic trading.
Third-party code. ForexR did not write, test or endorse this EA, and the summary above was generated automatically from its README and code. ForexR lists only repositories with readable source code and never hosts files. Read the code, backtest it and use a demo account first; automated trading can lose money quickly.
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