Merge pull request #161 from Aydinhamedi/main

sync

.github/workflows/auto_assign-issues.yml

@@ -0,0 +1,8 @@
+# If enabled, auto-assigns users when a new issue is created 
+# Defaults to true, allows you to install the app globally, and disable on a per-repo basis
+addAssignees: true
+
+# The list of users to assign to new issues. 
+# If empty or not provided, the repository owner is assigned
+assignees:
+  - Aydinhamedi

README.md

@@ -19,6 +19,14 @@
 > [!TIP]
 > If you just want the model go to the Github Releases.
 
+> [!NOTE]
+>  This model was built using the [EfficientNet ](https://github.com/qubvel/efficientnet) library,
+>  which is a collection of state-of-the-art models for image classification. To use the model,
+>  you need to install the library and import it as follows:
+> ```python
+> import efficientnet.tfkeras
+> ```
+
 The project includes a Command Line Interface (CLI) and a (GUI) Graphical User Interface for easy use of the model. The CLI, which is based on the [Python CLI template](https://github.com/Aydinhamedi/Python-CLI-template) from the same author, provides a user-friendly, colorful interface that allows you to interact with the model. you can fined the CLI in 
 
 ```
@@ -62,10 +70,10 @@ The model is a Convolutional Neural Network (CNN) trained on a dataset of 23681
 This combined dataset provides a comprehensive set of images for training the model.\
 
 ### Model list:
-| Model    | Base Model      | Params | acc    |
-|----------|-----------------|--------|--------|
-| V6       | efficientnet-b7 | 65.4M  | 97.12% |
-| V7 light | efficientnet-b4 | 29.7M  | 97.12% |
+| Model    | Base Model      | Params | acc    | Status |
+|----------|-----------------|--------|--------|--------|
+| V6       | efficientnet-b7 | 65.4M  | 97.12% |   ⚠️ (Not recommended) |
+| V7 light | efficientnet-b4 | 29.7M  | 97.12% |   ✅  |
 
 ## Training Methods
 ### The AI model supports two distinct training approaches: