Merge pull request #170 from Aydinhamedi/Beta-b

Beta b

.github/workflows/dependency-review.yml

@@ -15,6 +15,6 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: 'Checkout Repository'
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
       - name: 'Dependency Review'
-        uses: actions/dependency-review-action@v3
+        uses: actions/dependency-review-action@v4

.github/workflows/python-app.yml

@@ -20,9 +20,9 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
     - name: Install dependencies

.github/workflows/python-app_Alpha-b.yml

@@ -20,9 +20,9 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
     - name: Install dependencies

.github/workflows/python-app_Beta-b.yml

@@ -20,9 +20,9 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python 3.10
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v4
       with:
         python-version: "3.10"
     - name: Install dependencies

.gitignore

@@ -85,8 +85,12 @@ Samples/*
 /Interface/GUI/Data/logs
 
 # Other
-/Test_ENV_G.py
-/scc.exe
-/SCC_Auto.cmd
-/Microsoft.PowerShell_profile_Nvidia_smi.ps1
-/Data/image_SUB_generator.pkl
+/Test_ENV_G.py
+/scc.exe
+/SCC_Auto.cmd
+/Microsoft.PowerShell_profile_Nvidia_smi.ps1
+/Data/image_SUB_generator.pkl
+/GPU_Info.txt
+/Build.py
+/env
+/Temp

Create_requirements.cmd

@@ -1,4 +1,9 @@
 @echo off
-del requirements.txt >nul 2>&1
-pigar -l INFO generate
+del requirements.txt >nul  2>&1
+echo Y | pigar -l ERROR generate
 
+rem Use PowerShell to remove the first line of requirements.txt and save to a temporary file
+powershell -Command "Get-Content requirements.txt | Select-Object -Skip  2 | Set-Content requirements_temp.txt"
+
+rem Replace the original file with the modified temporary file
+move /Y requirements_temp.txt requirements.txt >nul

Interface/CLI/Data/Utils/FixedDropout.py

@@ -0,0 +1,19 @@
+from tensorflow.keras import layers, backend
+
+class FixedDropout(layers.Dropout):
+    def _get_noise_shape(self, inputs):
+        if self.noise_shape is None:
+            return self.noise_shape
+
+        symbolic_shape = backend.shape(inputs)
+        noise_shape = [symbolic_shape[axis] if shape is None else shape
+                       for axis, shape in enumerate(self.noise_shape)]
+        return tuple(noise_shape)
+
+    def get_config(self):
+        config = super().get_config()
+        return config
+
+    @classmethod
+    def from_config(cls, config):
+        return cls(**config)

Interface/CLI/Data/Utils/Other.py

@@ -1,12 +1,45 @@
+from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
 from Utils.print_color_V2_NEW import print_Color_V2
 from Utils.print_color_V1_OLD import print_Color
+from tabulate import tabulate
+from numba import cuda
+import numpy as np
 import pickle
 import gzip
+
+def GPU_memUsage(Print=True):
+    """Prints GPU memory usage for each GPU.
 
+    Args:
+    Print (bool): Whether to print the memory usage. 
+        If True, prints the memory usage. 
+        If False, returns the free and total memory as a tuple.
+
+    Returns:
+    If Print is False, returns a tuple (free, total) with the free 
+    and total memory in bytes for the GPU.
+    """
+    gpus = cuda.gpus.lst
+    for gpu in gpus:
+        with gpu:
+            meminfo = cuda.current_context().get_memory_info()
+            if Print:
+                print_Color(
+                    f'~*(GPU-MEM)~*--{gpu}--[free: {meminfo.free / (1024 ** 3):.2f}GB, used: {meminfo.total / (1024 ** 3) - meminfo.free / (1024 ** 3):.2f}GB, total, {meminfo.total / (1024 ** 3):.2f}GB]',
+                    ['green', 'cyan'],
+                    advanced_mode=True)
+            else:
+                return meminfo.free, meminfo.total
+
 def save_list(history, filename, compress=True):
-    # Saves the given history list to the specified filename.
-    # If compress is True, the file will be gzip compressed.
-    # Otherwise it will be saved as a normal pickle file.
+    """Saves a list to a file.
+
+    Args:
+        history: The list to save.
+        filename: The file to save the list to.
+        compress: Whether to gzip compress the file. Default is True.
+
+    """
     if compress:
         with gzip.open(filename, 'wb') as f:
             pickle.dump(history, f)
@@ -16,17 +49,69 @@ def save_list(history, filename, compress=True):
 
 
 def load_list(filename, compressed=True):
-    # Loads a pickled object from a file.
-    # If compressed=True, it will load from a gzip compressed file.
-    # Otherwise loads from a regular file.
+    """Loads a list from a file.
+
+    Args:
+        filename: The file to load from.
+        compressed: Whether the file is gzip compressed. Default is True.
+
+    Returns:
+        The loaded list from the file.
+    """
     if compressed:
         with gzip.open(filename, 'rb') as f:
             return pickle.load(f)
     else:
         with open(filename, 'rb') as f:
             return pickle.load(f)
+
+
 def P_warning(msg):
-    # Prints a warning message with color formatting.
-    # msg: The message to print as a warning.
+    """Prints a warning message to the console.
+
+    Args:
+        msg (str): The warning message to print.
+    """
     print_Color_V2(f'<light_red>Warning: <yellow>{msg}')
-
+
+def evaluate_model_full(y_test, model_pred, model=None, x_test=None):
+    """Evaluates a machine learning model on a test set.
+
+    Args:
+        x_test: Test set features.
+        y_test: Test set labels.  
+        model_pred: Model predictions.
+        model: The model object.
+
+    Returns:
+        None. Prints a table with accuracy, precision, recall and 
+        F1 score.
+    """
+    # Get the model predictions
+    if model_pred is None:
+        y_pred = model.predict(x_test)
+    else:
+        y_pred = model_pred
+
+    # Convert one-hot encoded predictions and labels to label encoded form
+    y_pred_bin = np.argmax(y_pred, axis=1)
+    y_test_bin = np.argmax(y_test, axis=1)
+
+    # Calculate normal metrics
+    accuracy = accuracy_score(y_test_bin, y_pred_bin)
+
+    # Calculate weighted metrics
+    weighted_precision = precision_score(
+        y_test_bin, y_pred_bin, average='macro')
+    weighted_f1 = f1_score(y_test_bin, y_pred_bin, average='macro')
+    weighted_recall = recall_score(y_test_bin, y_pred_bin, average='macro')
+
+    # Prepare data for the table
+    metrics = [["Accuracy", round(accuracy * 100, 6)],
+               ["Precision", round(weighted_precision * 100, 6)],
+               ["F1 Score", round(weighted_f1 * 100, 6)],
+               ["Recall", round(weighted_recall * 100, 6)]]
+
+    # Print the table
+    print(tabulate(metrics, headers=["Metric", "Value"], tablefmt="pretty"))
+

Interface/CLI/Data/Utils/README.md

@@ -2,14 +2,24 @@
 
 ## one_cycle_lr and lr_find (by 'benihime91') 
 - ### github repo used: [one_cycle_lr-tensorflow](https://github.com/benihime91/one_cycle_lr-tensorflow/tree/master)
-  - ### doc link: [1_README.md](docs\1_README.md)
+  - ### doc link: [1_README.md](docs/1_README.md)
 
 ## Python-color-print-V2 and Python-color-print (by Me)
 - ### github repo used(Python-color-print-V2): [Python-color-print-V2](https://github.com/Aydinhamedi/Python-color-print-V2)
-  - ### doc link: [2_README.md](docs\2_README.md)
+  - ### doc link: [2_README.md](docs/2_README.md)
 - ### github repo used(Python-color-print): [Python-color-print](https://github.com/Aydinhamedi/Python-color-print)
-  - ### doc link: [3_README.md](docs\3_README.md)
+  - ### doc link: [3_README.md](docs/3_README.md)
 
 ## Grad_cam (by GPT-4 😁)
 
 ## Other.py (by Me)
+
+## FixedDropout.py (by Me)
+For EfficientNet model. Example:
+```python
+from Utils.FixedDropout import FixedDropout
+from keras.models import load_model
+
+# Load the model
+model = load_model('PAI_model_T.h5', custom_objects={'FixedDropout': FixedDropout})
+```