adapted start scripts with parameter to download and use sample data instead of randomly generating data for fast demo purposes and increased tensorflow and pillow versions to address security issues

Author: julrog

README.md

@@ -21,8 +21,16 @@ Artificial neural networks is a popular field of research in artificial intellig
 2. Create a neural network model and process it. An example of this process is given in `examples/process_mnist_model.py` on [MNIST](http://yann.lecun.com/exdb/mnist/) data.
 3. Start the visualization tool `start_tool.py` and select the neural network via `Load Processed Network` to render the representation of the neural network.
 
+Or
+
+1. Run `start_tool.py --demo` to download data of an already processed model and render it.
+
 Multiple scripts are located in `examples`, which can be adapted to create and process neural networks. `examples/evaluation_plots.py` for example can be used to recreate the evaluation data and plots of my thesis.
 
+### Sample Model Importance
+
+A processed model can be found [here](https://drive.google.com/file/d/1LiVzBfB7LPrR95q_VO44wx4MyGNTj6vD/view?usp=sharing).
+
 ## Rendering Tool
 The visualization tool `start_tool.py` can be used to render and/or process neural networks. Instead of existing ones, you can also generate random networks and process them of various sizes. For neural networks the visualization results in a more structured view of a neural network in regards to their trained parameters compared to the most common ones.
 

VR_TOOL.md

@@ -21,6 +21,10 @@ This tool can be used to render a processed neural network in VR.
 
 * `python start_tool_vr.py`
 
+Or
+
+* Run `start_tool.py --demo` to download data of an already processed model and render it.
+
 ## Controls
 
 Using Oculus Quest 2 controller:
@@ -35,7 +39,7 @@ Using Oculus Quest 2 controller:
 
 
 ### GUI
-See [README.md](./README.md)) for information on the desktop GUI
+See [README.md](./README.md) for information on the desktop GUI
 
 ## Used Systems
 

configs/processing.json

@@ -4,7 +4,7 @@
   "layer_distance": 0.4,
   "layer_width": 1.0,
   "node_bandwidth_reduction": 0.95,
-  "prune_percentage": 0.0,
+  "prune_percentage": 0.9,
   "sampling_rate": 15.0,
   "smoothing": true,
   "smoothing_iterations": 8

configs/window.json

@@ -5,8 +5,8 @@
   "monitor_id": 0,
   "screen_height": 900,
   "screen_width": 1600,
-  "screen_x": 2765,
-  "screen_y": 127,
+  "screen_x": 1644,
+  "screen_y": 237,
   "title": "NNVis Render",
   "width": 1600
 }

gui/ui_window.py

@@ -79,10 +79,11 @@ def save_processed_nn_file(self) -> None:
     def open_processed_nn_file(self) -> None:
         filename = filedialog.askopenfilename(initialdir=DATA_PATH, title='Select A File',
                                               filetypes=(('processed nn files', '*.pro.npz'),))
-        data_loader: ProcessedNNHandler = ProcessedNNHandler(filename)
-        self.settings['network_name'] = ntpath.basename(
-            filename) + '_processed'
-        self.update_layer(data_loader.layer_data, processed_nn=data_loader)
+        if filename != '':
+            data_loader: ProcessedNNHandler = ProcessedNNHandler(filename)
+            self.settings['network_name'] = ntpath.basename(
+                filename) + '_processed'
+            self.update_layer(data_loader.layer_data, processed_nn=data_loader)
 
     def open_importance_file(self) -> None:
         filename = filedialog.askopenfilename(initialdir=DATA_PATH, title='Select A File',

requirements.txt

@@ -2,9 +2,10 @@ glfw==2.0.0
 matplotlib==3.3.3
 numpy==1.23.5
 pandas==1.2.0
-Pillow==9.0.1
+Pillow==9.3.0
 progressbar2==3.53.1
 PyOpenGL==3.1.5
 pyrr==0.10.3
 scikit_learn==0.24.0
-tensorflow==2.9.2
+tensorflow==2.9.3
+wget==3.2

requirements_vr.txt

@@ -3,9 +3,10 @@ matplotlib==3.3.3
 numpy==1.23.5
 openvr
 pandas==1.2.0
-Pillow==9.0.1
+Pillow==9.3.0
 progressbar2==3.53.1
 PyOpenGL==3.1.5
 pyrr==0.10.3
 scikit_learn==0.24.0
-tensorflow==2.9.2
+tensorflow==2.9.3
+wget==3.2

start_tool.py

@@ -1,11 +1,17 @@
 import logging
+import ntpath
+import os
 import threading
 import time
+import zipfile
+from argparse import ArgumentParser
 from typing import Optional
 
+import wget
 from OpenGL.GL import GL_MAJOR_VERSION, GL_MINOR_VERSION, glGetIntegerv
 
-from definitions import CameraPose
+from data.data_handler import ProcessedNNHandler
+from definitions import DATA_PATH, CameraPose
 from gui.constants import StatisticLink
 from gui.ui_window import OptionGui
 from opengl_helper.screenshot import create_screenshot
@@ -15,13 +21,34 @@
 from utility.performance import track_time
 from utility.window import Window, WindowHandler
 
-global options_gui
-options_gui = OptionGui()
-setup_logger('tool')
+
+def download_and_unzip_sample() -> str:
+    output_directory = DATA_PATH
+    filename = wget.download(
+        'https://drive.google.com/uc?export=download&id=1LiVzBfB7LPrR95q_VO44wx4MyGNTj6vD', out=output_directory)
+    zip_filepath = os.path.join(output_directory, filename)
+    with zipfile.ZipFile(zip_filepath, 'r') as zip_ref:
+        zip_ref.extractall(DATA_PATH)
+    return os.path.join(DATA_PATH, 'sample_model.npz')
+
+
+def open_processed_network(option_gui: OptionGui, filename: str) -> None:
+    data_loader: ProcessedNNHandler = ProcessedNNHandler(filename)
+    option_gui.processing_config['prune_percentage'] = 0.9
+    option_gui.processing_setting.set()
+    option_gui.settings['network_name'] = ntpath.basename(
+        filename) + '_processed'
+    option_gui.update_layer(data_loader.layer_data, processed_nn=data_loader)
 
 
 def compute_render(some_name: str) -> None:
     global options_gui
+    global use_sample
+
+    if use_sample:
+        global sample_filepath
+        logging.info('Loading sample model...')
+        open_processed_network(options_gui, sample_filepath)
 
     width, height = 1920, 1200
 
@@ -72,6 +99,7 @@ def frame() -> None:
     if not options_gui.settings['Closed']:
         print('Start building network: ' +
               str(options_gui.settings['current_layer_data']))
+        options_gui.settings['update_model'] = False
         network_processor = NetworkProcessor(options_gui.settings['current_layer_data'],
                                              options_gui.processing_config,
                                              importance_data=options_gui.settings['importance_data'],
@@ -154,9 +182,39 @@ def frame() -> None:
     options_gui.destroy()
 
 
-compute_render_thread: threading.Thread = threading.Thread(
-    target=compute_render, args=(1,))
-compute_render_thread.setDaemon(True)
-compute_render_thread.start()
+def parse_args() -> bool:
+    parser = ArgumentParser(prog='Start nn_vis tool')
+    parser.add_argument('--demo', action='store_true',
+                        help='Download sample of a processed model and render it with 90% pruned edges instead of generating a random model.')
+    args = parser.parse_args()
+    return args.demo
+
 
-options_gui.start()
+if __name__ == '__main__':
+    global options_gui
+    options_gui = OptionGui()
+
+    global sample_filepath
+    sample_filepath = 'sample_model.npz'
+
+    global use_sample
+    use_sample = parse_args()
+
+    setup_logger('tool')
+
+    if use_sample:
+        expected_sample_path = os.path.join(DATA_PATH, sample_filepath)
+        if not os.path.exists(expected_sample_path):
+            logging.info(
+                f'Downloading sample model to "{expected_sample_path}". This might take a minute ...')
+            sample_filepath = download_and_unzip_sample()
+        else:
+            logging.info(
+                f'Using sample model at "{expected_sample_path}"')
+            sample_filepath = expected_sample_path
+    compute_render_thread: threading.Thread = threading.Thread(
+        target=compute_render, args=(1,))
+    compute_render_thread.setDaemon(True)
+    compute_render_thread.start()
+
+    options_gui.start()

start_tool_vr.py

@@ -1,10 +1,17 @@
 import logging
+import ntpath
+import os
 import threading
 import time
+import zipfile
+from argparse import ArgumentParser
 from typing import List, Optional, Tuple
 
+import wget
 from OpenGL.GL import GL_MAJOR_VERSION, GL_MINOR_VERSION, glGetIntegerv
 
+from data.data_handler import ProcessedNNHandler
+from definitions import DATA_PATH
 from gui.constants import StatisticLink
 from gui.ui_window import OptionGui
 from processing.network_processing import NetworkProcessor
@@ -13,15 +20,36 @@
 from utility.performance import track_time
 from vr.vr_handler import VRHandler
 
-global options_gui
-options_gui = OptionGui()
-setup_logger('tool')
-
 RENDER_MODES: List[Tuple[int, int]] = [(3, 2), (4, 1), (1, 1), (2, 2)]
 
 
+def download_and_unzip_sample() -> str:
+    output_directory = DATA_PATH
+    filename = wget.download(
+        'https://drive.google.com/uc?export=download&id=1LiVzBfB7LPrR95q_VO44wx4MyGNTj6vD', out=output_directory)
+    zip_filepath = os.path.join(output_directory, filename)
+    with zipfile.ZipFile(zip_filepath, 'r') as zip_ref:
+        zip_ref.extractall(DATA_PATH)
+    return os.path.join(DATA_PATH, 'sample_model.npz')
+
+
+def open_processed_network(option_gui: OptionGui, filename: str) -> None:
+    data_loader: ProcessedNNHandler = ProcessedNNHandler(filename)
+    option_gui.processing_config['prune_percentage'] = 0.9
+    option_gui.processing_setting.set()
+    option_gui.settings['network_name'] = ntpath.basename(
+        filename) + '_processed'
+    option_gui.update_layer(data_loader.layer_data, processed_nn=data_loader)
+
+
 def compute_render(_: str) -> None:
     global options_gui
+    global use_sample
+
+    if use_sample:
+        global sample_filepath
+        logging.info('Loading sample model...')
+        open_processed_network(options_gui, sample_filepath)
 
     FileHandler().read_statistics()
 
@@ -101,6 +129,7 @@ def frame() -> None:
             'Start building network: ' +
             str(options_gui.settings['current_layer_data'])
         )
+        options_gui.settings['update_model'] = False
         network_processor = NetworkProcessor(
             options_gui.settings['current_layer_data'],
             options_gui.processing_config,
@@ -191,10 +220,39 @@ def frame() -> None:
     options_gui.destroy()
 
 
-compute_render_thread: threading.Thread = threading.Thread(
-    target=compute_render, args=(1,)
-)
-compute_render_thread.setDaemon(True)
-compute_render_thread.start()
+def parse_args() -> bool:
+    parser = ArgumentParser(prog='Start nn_vis tool for VR')
+    parser.add_argument('--demo', action='store_true',
+                        help='Download sample of a processed model and render it with 90% pruned edges instead of generating a random model.')
+    args = parser.parse_args()
+    return args.demo
+
+
+if __name__ == '__main__':
+    global options_gui
+    options_gui = OptionGui()
+
+    global sample_filepath
+    sample_filepath = 'sample_model.npz'
+
+    global use_sample
+    use_sample = parse_args()
+
+    setup_logger('tool_vr')
+
+    if use_sample:
+        expected_sample_path = os.path.join(DATA_PATH, sample_filepath)
+        if not os.path.exists(expected_sample_path):
+            logging.info(
+                f'Downloading sample model to "{expected_sample_path}". This might take a minute ...')
+            sample_filepath = download_and_unzip_sample()
+        else:
+            logging.info(
+                f'Using sample model at "{expected_sample_path}"')
+            sample_filepath = expected_sample_path
+    compute_render_thread: threading.Thread = threading.Thread(
+        target=compute_render, args=(1,))
+    compute_render_thread.setDaemon(True)
+    compute_render_thread.start()
 
-options_gui.start()
+    options_gui.start()