Merge pull request #196 from Aydinhamedi/Alpha-b

Alpha b
Aydinhamedi · Mar 14, 2024 · 17802d3 · 17802d3
2 parents edf9cd1 + 12b754d
commit 17802d3
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diff --git a/.github/workflows/ruff_L&F.yml b/.github/workflows/ruff_L&F.yml
@@ -26,7 +26,7 @@ jobs:
         pip install ruff
     - name: Lint with ruff
       run: |
-        ruff check . --fix --show-fixes --statistics
+        ruff check . --fix --show-fixes
     - name: Format with ruff
       run: |
         ruff format . --preview --line-length 140
diff --git a/BETA_E_Model_T&T.ipynb b/BETA_E_Model_T&T.ipynb
@@ -114,7 +114,7 @@
     "from Utils.Grad_cam import make_gradcam_heatmap\n",
     "from Utils.print_color_V2_NEW import print_Color_V2\n",
     "from Utils.print_color_V1_OLD import print_Color\n",
-    "from Utils.Other import * # noqa: F403\n",
+    "from Utils.Other import *  # noqa: F403\n",
     "\n",
     "# Other\n",
     "tf.get_logger().setLevel(\"ERROR\")\n",
@@ -3214,10 +3214,12 @@
     "        layer.trainable = True\n",
     "\n",
     "    # Combine the output of the two base models\n",
-    "    combined = concatenate([\n",
-    "        Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model1_out)),\n",
-    "        Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model2_out)),\n",
-    "    ])\n",
+    "    combined = concatenate(\n",
+    "        [\n",
+    "            Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model1_out)),\n",
+    "            Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model2_out)),\n",
+    "        ]\n",
+    "    )\n",
     "\n",
     "    # adding CDL\n",
     "    Dense_L1 = Dense(1024, activation=\"relu\", kernel_regularizer=l2(0.02))(combined)\n",
@@ -9956,10 +9958,12 @@
     "\n",
     "        old_weights, old_biases = layer.get_weights()\n",
     "\n",
-    "        layer.set_weights([\n",
-    "            weight_initializer(shape=old_weights.shape),\n",
-    "            bias_initializer(shape=len(old_biases)),\n",
-    "        ])"
+    "        layer.set_weights(\n",
+    "            [\n",
+    "                weight_initializer(shape=old_weights.shape),\n",
+    "                bias_initializer(shape=len(old_biases)),\n",
+    "            ]\n",
+    "        )"
    ]
   },
   {
@@ -10356,14 +10360,14 @@
     "\n",
     "\n",
     "# Funcs\n",
-    "def normalize_TO_RANGE(arr, min_val, max_val): # noqa: F811\n",
+    "def normalize_TO_RANGE(arr, min_val, max_val):  # noqa: F811\n",
     "    arr = arr.astype(\"float32\")\n",
     "    arr = (arr - arr.min()) / (arr.max() - arr.min())\n",
     "    arr = arr * (max_val - min_val) + min_val\n",
     "    return arr\n",
     "\n",
     "\n",
-    "def Z_SCORE_normalize(arr): # noqa: F811\n",
+    "def Z_SCORE_normalize(arr):  # noqa: F811\n",
     "    arr = arr.astype(\"float32\")\n",
     "    mean = np.mean(arr)\n",
     "    std_dev = np.std(arr)\n",
@@ -10613,8 +10617,8 @@
     "    advanced_mode=True,\n",
     ")\n",
     "# warnings\n",
-    "P_warning(\"[RES_Train -> True].\") if RES_Train else None # noqa: F405\n",
-    "P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None # noqa: F405\n",
+    "P_warning(\"[RES_Train -> True].\") if RES_Train else None  # noqa: F405\n",
+    "P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None  # noqa: F405\n",
     "print_Color(\"Setup Verbose END.\", [\"yellow\"])\n",
     "# MAIN LOOP\n",
     "try:\n",
@@ -10636,7 +10640,7 @@
     "            advanced_mode=True,\n",
     "        )\n",
     "        # warnings\n",
-    "        P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None # noqa: F405\n",
+    "        P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None  # noqa: F405\n",
     "        # DP\n",
     "        if not AdvSubsetC:\n",
     "            print_Color(\"Shuffling data...\", [\"yellow\"])\n",
@@ -10860,7 +10864,7 @@
     "        # Garbage Collection (memory)\n",
     "        gc.collect()\n",
     "        tf.keras.backend.clear_session()\n",
-    "        GPU_memUsage() # noqa: F405\n",
+    "        GPU_memUsage()  # noqa: F405\n",
     "        # Update TF summary text\n",
     "        for Key in TF_Summary_text_Dict:\n",
     "            TF_Summary_text_cache = f\"# @[{Key}].Data:\\n\"\n",
@@ -11200,10 +11204,10 @@
     "from numba import cuda\n",
     "\n",
     "device = cuda.get_current_device()\n",
-    "GPU_memUsage() # noqa: F405\n",
+    "GPU_memUsage()  # noqa: F405\n",
     "print(\"Realising all memory...\")\n",
     "device.reset()\n",
-    "GPU_memUsage() # noqa: F405\n",
+    "GPU_memUsage()  # noqa: F405\n",
     "print(\"done.\")"
    ]
   },
@@ -11221,7 +11225,7 @@
    "outputs": [],
    "source": [
     "# Save history\n",
-    "save_list(history, \"history\\\\model_history.pkl.gz\", compress=True) # noqa: F405"
+    "save_list(history, \"history\\\\model_history.pkl.gz\", compress=True)  # noqa: F405"
    ]
   },
   {
@@ -11231,7 +11235,7 @@
    "outputs": [],
    "source": [
     "# load history\n",
-    "history = load_list(\"history\\\\model_history.pkl.gz\", compressed=True) # noqa: F405"
+    "history = load_list(\"history\\\\model_history.pkl.gz\", compressed=True)  # noqa: F405"
    ]
   },
   {
@@ -11705,9 +11709,9 @@
     "\n",
     "# Print acc\n",
     "print(\"Val data acc:\")\n",
-    "evaluate_model_full(y_val, val_predictions) # noqa: F405\n",
+    "evaluate_model_full(y_val, val_predictions)  # noqa: F405\n",
     "print(\"Test data acc:\")\n",
-    "evaluate_model_full(y_test, test_predictions) # noqa: F405\n",
+    "evaluate_model_full(y_test, test_predictions)  # noqa: F405\n",
     "\n",
     "# format data\n",
     "val_predictions = np.argmax(val_predictions, axis=1)\n",
@@ -11824,7 +11828,7 @@
     "    plt.title(\"Number of Incorrect Predictions vs. Number of Data Points\")\n",
     "    plt.show()\n",
     "except Exception:\n",
-    "    P_warning(\"Failed to plot incorrect predictions vs. data points\") # noqa: F405"
+    "    P_warning(\"Failed to plot incorrect predictions vs. data points\")  # noqa: F405"
    ]
   }
  ],

diff --git a/Interface/CLI/Data/CLI_main.py b/Interface/CLI/Data/CLI_main.py
@@ -29,7 +29,7 @@
 # Utils
 from Utils.Grad_cam import make_gradcam_heatmap
 from Utils.print_color_V1_OLD import print_Color
-from Utils.Other import * # noqa: F403
+from Utils.Other import *  # noqa: F403
 
 # global vars>>>
 # CONST SYS
@@ -463,7 +463,7 @@ def CI_tmwd(argv_Split: list = ["none"]):
             else:
                 print("Training the model...\n")
                 # training
-                model.fit(images, labels, epochs=train_epochs, batch_size=1, verbose="auto") 
+                model.fit(images, labels, epochs=train_epochs, batch_size=1, verbose="auto")
                 print("Training done.\n")
         else:
             print_Color(

diff --git a/Interface/GUI/Data/GUI_main.py b/Interface/GUI/Data/GUI_main.py
@@ -79,7 +79,7 @@
     sys.exit()
 # global vars>>>
 # CONST SYS
-GUI_Ver = "0.9.3 Pre1"
+GUI_Ver = "0.9.4"
 Model_dir = "Data/PAI_model"  # without file extention
 Database_dir = "Data/dataset.npy"
 IMG_AF = ("JPEG", "PNG", "BMP", "TIFF", "JPG", "DCM", "DICOM")
@@ -754,8 +754,8 @@ def main() -> None:
         if not event == "-TIMEOUT-":
             logger.debug(f"GUI_window:event: {event}")
             logger.debug(f"GUI_window:values: {values}")
-            print(f"GUI_window:event: {event}")
-            print(f"GUI_window:values: {values}")
+            print(f"GUI_window:event: ~e[{event}]e~\n")
+            print(f"GUI_window:values: ~v[{values}]v~\n")
 
         # Check if the window has been closed or the 'Close' button has been clicked
         if event == sg.WINDOW_CLOSED or event == "Close":
@@ -835,7 +835,7 @@ def main() -> None:
             # Retrieve the result from the queue
             result_expanded = ""
             result = GUI_Queue["-Main_log-"].get()
-            print(f"Queue Data: {result}")
+            print(f"Queue Data: {result}\n")
             logger.debug(f"Queue[-Main_log-]:get: {result}")
             # Update the GUI with the result message
             for block in result:

diff --git a/Interface/GUI/GUI.cmd b/Interface/GUI/GUI.cmd
@@ -57,8 +57,10 @@ for /F "usebackq delims==" %%i in ("Data\requirements.txt") do (
 REM Write the current Python version + Python install time to the file
 echo %current_python_version% > %PV_filepath%
 @REM Pause for user input
-echo Press any key to load the GUI...
-pause > nul
+if not "%Full_Auto%"=="1" (
+    echo Press any key to load the GUI...
+    pause > nul
+)
 
 :FAST_START
 REM Print the appropriate loading message

diff --git a/Interface/GUI/README.txt b/Interface/GUI/README.txt
diff --git a/Interface/GUI/Silent_Run.vbs b/Interface/GUI/Silent_Run.vbs
@@ -1,3 +1,18 @@
 Set WshShell = CreateObject("WScript.Shell")
-WshShell.Run chr(34) & "GUI.cmd" & Chr(34), 0
-Set WshShell = Nothing
+Set FSO = CreateObject("Scripting.FileSystemObject")
+
+' Define the path to the file you want to check
+filePath = "Data\Python Ver.tmp"
+
+' Check if the file exists
+If FSO.FileExists(filePath) Then
+    ' If the file exists, run it without showing a window
+    WshShell.Run chr(34) & "GUI.cmd" & Chr(34), 0, False
+Else
+    ' If the file does not exist, run GUI.cmd with a terminal window and show a popup message
+    WshShell.Run chr(34) & "GUI.cmd" & Chr(34), 1, False
+    WshShell.Popup "This is the first time running the GUI. It may take a few minutes to start.", 30, "First Time Running", 64
+End If
+
+Set WshShell = Nothing
+Set FSO = Nothing
diff --git a/Model_T&T.ipynb b/Model_T&T.ipynb
@@ -114,7 +114,7 @@
     "from Utils.Grad_cam import make_gradcam_heatmap\n",
     "from Utils.print_color_V2_NEW import print_Color_V2\n",
     "from Utils.print_color_V1_OLD import print_Color\n",
-    "from Utils.Other import * # noqa: F403\n",
+    "from Utils.Other import *  # noqa: F403\n",
     "\n",
     "# Other\n",
     "tf.get_logger().setLevel(\"ERROR\")\n",
@@ -3214,10 +3214,12 @@
     "        layer.trainable = True\n",
     "\n",
     "    # Combine the output of the two base models\n",
-    "    combined = concatenate([\n",
-    "        Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model1_out)),\n",
-    "        Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model2_out)),\n",
-    "    ])\n",
+    "    combined = concatenate(\n",
+    "        [\n",
+    "            Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model1_out)),\n",
+    "            Dense(512, activation=\"relu\", kernel_regularizer=l2(0.01))(GlobalAveragePooling2D()(base_model2_out)),\n",
+    "        ]\n",
+    "    )\n",
     "\n",
     "    # adding CDL\n",
     "    Dense_L1 = Dense(1024, activation=\"relu\", kernel_regularizer=l2(0.02))(combined)\n",
@@ -9956,10 +9958,12 @@
     "\n",
     "        old_weights, old_biases = layer.get_weights()\n",
     "\n",
-    "        layer.set_weights([\n",
-    "            weight_initializer(shape=old_weights.shape),\n",
-    "            bias_initializer(shape=len(old_biases)),\n",
-    "        ])"
+    "        layer.set_weights(\n",
+    "            [\n",
+    "                weight_initializer(shape=old_weights.shape),\n",
+    "                bias_initializer(shape=len(old_biases)),\n",
+    "            ]\n",
+    "        )"
    ]
   },
   {
@@ -10356,14 +10360,14 @@
     "\n",
     "\n",
     "# Funcs\n",
-    "def normalize_TO_RANGE(arr, min_val, max_val): # noqa: F811\n",
+    "def normalize_TO_RANGE(arr, min_val, max_val):  # noqa: F811\n",
     "    arr = arr.astype(\"float32\")\n",
     "    arr = (arr - arr.min()) / (arr.max() - arr.min())\n",
     "    arr = arr * (max_val - min_val) + min_val\n",
     "    return arr\n",
     "\n",
     "\n",
-    "def Z_SCORE_normalize(arr): # noqa: F811\n",
+    "def Z_SCORE_normalize(arr):  # noqa: F811\n",
     "    arr = arr.astype(\"float32\")\n",
     "    mean = np.mean(arr)\n",
     "    std_dev = np.std(arr)\n",
@@ -10613,8 +10617,8 @@
     "    advanced_mode=True,\n",
     ")\n",
     "# warnings\n",
-    "P_warning(\"[RES_Train -> True].\") if RES_Train else None # noqa: F405\n",
-    "P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None # noqa: F405\n",
+    "P_warning(\"[RES_Train -> True].\") if RES_Train else None  # noqa: F405\n",
+    "P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None  # noqa: F405\n",
     "print_Color(\"Setup Verbose END.\", [\"yellow\"])\n",
     "# MAIN LOOP\n",
     "try:\n",
@@ -10636,7 +10640,7 @@
     "            advanced_mode=True,\n",
     "        )\n",
     "        # warnings\n",
-    "        P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None # noqa: F405\n",
+    "        P_warning(\"[TerminateOnHighTemp_M -> False] GPU temperature protection is OFF\") if not TerminateOnHighTemp_M else None  # noqa: F405\n",
     "        # DP\n",
     "        if not AdvSubsetC:\n",
     "            print_Color(\"Shuffling data...\", [\"yellow\"])\n",
@@ -10860,7 +10864,7 @@
     "        # Garbage Collection (memory)\n",
     "        gc.collect()\n",
     "        tf.keras.backend.clear_session()\n",
-    "        GPU_memUsage() # noqa: F405\n",
+    "        GPU_memUsage()  # noqa: F405\n",
     "        # Update TF summary text\n",
     "        for Key in TF_Summary_text_Dict:\n",
     "            TF_Summary_text_cache = f\"# @[{Key}].Data:\\n\"\n",
@@ -11200,10 +11204,10 @@
     "from numba import cuda\n",
     "\n",
     "device = cuda.get_current_device()\n",
-    "GPU_memUsage() # noqa: F405\n",
+    "GPU_memUsage()  # noqa: F405\n",
     "print(\"Realising all memory...\")\n",
     "device.reset()\n",
-    "GPU_memUsage() # noqa: F405\n",
+    "GPU_memUsage()  # noqa: F405\n",
     "print(\"done.\")"
    ]
   },
@@ -11221,7 +11225,7 @@
    "outputs": [],
    "source": [
     "# Save history\n",
-    "save_list(history, \"history\\\\model_history.pkl.gz\", compress=True) # noqa: F405"
+    "save_list(history, \"history\\\\model_history.pkl.gz\", compress=True)  # noqa: F405"
    ]
   },
   {
@@ -11231,7 +11235,7 @@
    "outputs": [],
    "source": [
     "# load history\n",
-    "history = load_list(\"history\\\\model_history.pkl.gz\", compressed=True) # noqa: F405"
+    "history = load_list(\"history\\\\model_history.pkl.gz\", compressed=True)  # noqa: F405"
    ]
   },
   {
@@ -11705,9 +11709,9 @@
     "\n",
     "# Print acc\n",
     "print(\"Val data acc:\")\n",
-    "evaluate_model_full(y_val, val_predictions) # noqa: F405\n",
+    "evaluate_model_full(y_val, val_predictions)  # noqa: F405\n",
     "print(\"Test data acc:\")\n",
-    "evaluate_model_full(y_test, test_predictions) # noqa: F405\n",
+    "evaluate_model_full(y_test, test_predictions)  # noqa: F405\n",
     "\n",
     "# format data\n",
     "val_predictions = np.argmax(val_predictions, axis=1)\n",
@@ -11824,7 +11828,7 @@
     "    plt.title(\"Number of Incorrect Predictions vs. Number of Data Points\")\n",
     "    plt.show()\n",
     "except Exception:\n",
-    "    P_warning(\"Failed to plot incorrect predictions vs. data points\") # noqa: F405"
+    "    P_warning(\"Failed to plot incorrect predictions vs. data points\")  # noqa: F405"
    ]
   }
  ],

diff --git a/history_vis.py b/history_vis.py
@@ -1,9 +1,9 @@
-from Utils.Other import * # noqa: F403
+from Utils.Other import *  # noqa: F403
 import matplotlib.pyplot as plt
 import numpy as np
 
 # load history
-history = load_list("history\\model_history.pkl.gz", compressed=True) # noqa: F405
+history = load_list("history\\model_history.pkl.gz", compressed=True)  # noqa: F405
 
 # Chunk size for 3D plot
 chunk_size = 6  # Change this to your desired chunk size

diff --git a/requirements.txt b/requirements.txt
@@ -1,4 +1,3 @@
-absl-py==1.4.0
 adabelief-tf==0.2.1
 efficientnet==1.1.1
 gpu-control==1.0.0