Preparing to use cloud, upgrade device agnostic code

.gitignore

@@ -3,7 +3,7 @@
 .mypy_cache/
 __pycache__/
 
-dataset/
+emotion_recognition_data/
 test_result/
 git_file_ignore*
 

DeepLearning/model.py

@@ -1,7 +1,7 @@
 import torch
 import os
 from pathlib import Path
-from DeepLearning.settings import learning_rate
+from DeepLearning.settings import learning_rate, pytorch_device
 
 
 class EmotionClassificationModel(torch.nn.Module):
@@ -70,7 +70,7 @@ def BackupModel(self, folder_path: str, file_name: str) -> None:
     torch.save(self.state_dict(), os.path.join(folder_path, file_name))
 
   def LoadModel(self, path_to_model: str) -> None:
-    self.load_state_dict(torch.load(path_to_model))
+    self.load_state_dict(torch.load(path_to_model, map_location=torch.device(pytorch_device)))
     self.eval()
     self.optimizer = self.CreateOptimizer()  # optimizer must be recreated after load
 

README.md

@@ -33,19 +33,20 @@ if ~~crossed~~ means left undone
   - [x] Camera capture
   - [ ] Create chat tab
   - [x] Real time camera
+  - [ ] Create cloud storage sync tab
 - [ ] Poe.api (chatting with bots)
 - [x] ~~Camera module (using cv2)~~
 (reason: currently camera function are not shared between modules, so they are written directly in gui module)
 - [x] Base of pre-trained ML models module
   - [x] Downloaded face detection and landmark detection models
-- [ ] Web server learning module (?)
+- [ ] Backup dataset and pre-trained modules on mega.nz
 - [x] Dlib, set up for using cuda
 
 ## Requirements
 
 ### Cuda
 
-This project uses cuda 11.8. You should install it on your own, but you might want to visit [cuda 11.8 toolkit download page](https://developer.nvidia.com/cuda-11-8-0-download-archive) and [cudann archive page](https://developer.nvidia.com/rdp/cudnn-archive).
+This project uses cuda 11.8 (but you can try using newer version). You should install it on your own, but you might want to visit [cuda 11.8 toolkit download page](https://developer.nvidia.com/cuda-11-8-0-download-archive) and [cudann archive page](https://developer.nvidia.com/rdp/cudnn-archive).
 
 If your os is ubuntu, you can use [this guide](https://medium.com/@gokul.a.krishnan/how-to-install-cuda-cudnn-and-tensorflow-on-ubuntu-22-04-2023-20fdfdb96907) to install cuda + cudann.
 
@@ -90,9 +91,15 @@ Invalid handle. Cannot load symbol cublasLtCreate
 
 If you also encounter this error, you need to install [libcublasLt.so.12](https://packages.debian.org/trixie/amd64/libcublaslt12/download).
 
-### opencv
+### Required python packages
 
-```pip3 install cv2```
+Just run the following command:
+
+```pip3
+pip3 install -r requirements.txt
+```
+
+***IMPORTANT:*** ```requirements.txt``` does not include **dlib** and **pytorch** package
 
 ### Dataset
 

requirements.txt

@@ -0,0 +1,5 @@
+numpy
+cv2
+pyqtgraph
+PySide6
+megapy

shared.py

@@ -1,11 +1,12 @@
 from sys import argv
 from os import path
 
-data_folder = "data/"
-dataset_folder = "dataset/"
-pretrained_face_landmarks_predictor_model = data_folder + "shape_predictor_68_face_landmarks.dat"
-pretrained_face_detector = data_folder + "mmod_human_face_detector.dat"
-pretrained_emotion_recognition_model = data_folder + "emotion_recognition_model.pt"
+
+data_folder_path = "emotion_recognition_data/"
+dataset_folder_path = data_folder_path + "dataset/"
+pretrained_face_landmarks_predictor_model = data_folder_path + "shape_predictor_68_face_landmarks.dat"
+pretrained_face_detector = data_folder_path + "mmod_human_face_detector.dat"
+pretrained_emotion_recognition_model = data_folder_path + "emotion_recognition_model.pt"
 
 
 def GetRelativePath(var):