modified:

README.md

@@ -28,14 +28,14 @@ The data set covers four measurement series. Labels are provided as destructive
 ### Requirements
  - Python 3.10
  - PyTorch 1.11.0
-and the packages defined in the requirements file (```pip3 install -r requirements.txt```)
+and the packages defined in the requirements file (```pip install -r requirements.txt```)
  - Download the data set to a local folder
 
 ## How to train
 If all packages are installed and the data set was downloaded, the training can start.
 This will train the HS-CNN model on the ripeness classification of avocados:
 
-    PYTHONPATH=$PYTHONPATH:. python3 classification/train.py --data_path /folder/of/downloaded/dataset/ --model deephs_net --fruit avocado --classification_type ripeness --seed 23312323
+    PYTHONPATH=$PYTHONPATH:. python classification/train.py --data_path "D:\College\Project" --model deephs_net --fruit mango --classification_type ripeness --seed 23312323 --log_path "D:\College\Project\test_log_path" --num_epochs 2
 
 <img src="images/deephs_net_loss.png" alt="Loss" style="width: 300px;"/><br>
 <img src="images/deephs_net_accuracy.png" alt="Accuracy" style="width: 300px;"/><br>
@@ -51,7 +51,7 @@ And this will train HS-CNN + HyveConv++ on the same classification task:
 <img src="images/hyve_confusion.png" alt="Confusion" style="width: 300px;"/><br>
 **Figure 2** - Training of HS-CNN + HyveConv++:
 
-```PYTHONPATH=$PYTHONPATH:. python3 classification/train.py --help``` provides helpful information regarding the parameters. 
+```PYTHONPATH=$PYTHONPATH:. python classification/train.py --help``` provides helpful information regarding the parameters. 
 For more information about the training framework PyTorch-Lightning, we refer to the official documentation (https://pytorch-lightning.readthedocs.io/en/latest/).
 
 

classification/train.py

@@ -1,9 +1,14 @@
+
+#get cpu num core py os
+import os
+
+
 import argparse
 
 import pytorch_lightning as lightning
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
-from pytorch_lightning.loggers.wandb import WandbLogger
+from pytorch_lightning.loggers import WandbLogger
 import torch
 from torch.utils.data import DataLoader
 from torchvision import transforms 
@@ -26,6 +31,14 @@
 )
 import core.util as util
 
+import wandb
+import torch
+
+
+
+
+
+
 AUGMENTATION_CONFIG_TRAIN = {
     'random_flip': True,
     'random_rotate': True,
@@ -321,7 +334,7 @@ def str2bool(v):
                         help="the root folder of dataset")
     parser.add_argument("--seed", type=int, default=0)
     parser.add_argument("--log_path", type=str, default=None)
-    parser.add_argument("--online_logging", default=False, action='store_true')
+    parser.add_argument("--online_logging", default=True, action='store_true') #online logging true
     parser.add_argument("--debug", default=False, action='store_true')
     parser.add_argument("--model_checkpoint", default=None, type=str)
 
@@ -363,8 +376,12 @@ def main(hparams):
     print("Hparams: %s" % hparams)
 
     model = DeepHsModule(hparams)
-    logger = WandbLogger(offline=not hparams['online_logging'], save_dir=hparams['log_path'],
-                         project='deephs') if 'logger' not in hparams.keys() else hparams['logger']
+    logger = WandbLogger(
+    offline=not hparams.get('online_logging', True),  # Use parentheses here
+    save_dir=hparams.get('log_path', './logs'),
+    project='deephs') if 'logger' not in hparams else hparams['logger']
+
+
 
     early_stop_callback = EarlyStopping(
         monitor='val/loss',
@@ -382,12 +399,17 @@ def main(hparams):
         mode='min'
     )
 
+
+
+
+
+    num_cpu_cores = os.cpu_count() #ใช้ cpu 
     trainer = lightning.Trainer(max_epochs=opt.num_epochs,
-                                accelerator='gpu',
-                                devices=-1,
+                                accelerator='cpu',
+                                devices=1,
                                 logger=logger,
-                                strategy='ddp',
-                                min_epochs=50,
+                                strategy=None,
+                                min_epochs=2,
                                 callbacks=[LRLoggingCallback(),
                                            early_stop_callback,
                                            checkpoint_callback
@@ -408,7 +430,8 @@ def main(hparams):
 
 if __name__ == "__main__":
     opt = get_args()
-    num_gpus = torch.cuda.device_count()
+    #ปิด gpu
+    #num_gpus = torch.cuda.device_count()
 
     # fix the seed for reproducibility
     seed = opt.seed

classification/train_multi_camera.py

@@ -211,7 +211,7 @@ def main(hparams):
         mode='min'
     )
 
-    trainer = lightning.Trainer(max_epochs=opt.num_epochs, gpus=-1, logger=logger,
+    trainer = lightning.Trainer(max_epochs=opt.num_epochs, gpus=0, logger=logger,
                                 strategy='ddp',
                                 min_epochs=50,
                                 callbacks=[LRLoggingCallback(),

requirements.txt

@@ -1,4 +1,10 @@
-h5py==2.10.0
+#upgrade h5py ,wandb,pytorch-lightning
+#hey
+h5py==3.11.0
+wandb==0.18.0
+pytorch-lightning==1.5.10
+
+#classic
 image==1.5.32
 imageio==2.8.0
 matplotlib==3.5.3
@@ -8,7 +14,6 @@ opencv-python==4.6.0.66
 PyExifTool==0.1.1
 pyparsing==3.0.9
 python-dateutil==2.8.2
-pytorch-lightning==1.7.6
 scikit-image==0.19.2
 scikit-learn==1.0.2
 scipy==1.8.0
@@ -26,6 +31,6 @@ torchvision==0.12.0
 tornado==6.2
 tqdm==4.64.1
 urllib3==1.26.12
-wandb==0.13.3
+
 
 

run_tracking.py

@@ -0,0 +1 @@
+

test_gpu_.py

@@ -0,0 +1,17 @@
+'''
+import torch
+import pytorch_lightning as pl
+print(torch.__version__)
+print(pl.__version__)
+'''
+import torch
+import os
+#print(f"MASTER_ADDR: {os.getenv('MASTER_ADDR')}")
+#print(f"MASTER_PORT: {os.getenv('MASTER_PORT')}")
+
+#print(os.cpu_count())
+
+
+
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+print(device)

wandb/offline-run-20240916_141122-l9un9d3d/files/config.yaml

@@ -0,0 +1,25 @@
+_wandb:
+    value:
+        cli_version: 0.18.0
+        m: []
+        python_version: 3.10.0
+        t:
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+            "4": 3.10.0
+            "5": 0.18.0
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+            "12": 0.18.0
+            "13": windows-amd64

wandb/offline-run-20240916_141122-l9un9d3d/files/requirements.txt

@@ -0,0 +1,97 @@
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+aiohappyeyeballs==2.4.0
+aiohttp==3.10.5
+aiosignal==1.3.1
+asgiref==3.8.1
+async-timeout==4.0.3
+attrs==24.2.0
+cachetools==5.5.0
+certifi==2024.8.30
+charset-normalizer==3.3.2
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+colorama==0.4.6
+cycler==0.12.1
+Django==5.1.1
+docker-pycreds==0.4.0
+filelock==3.16.0
+fonttools==4.53.1
+frozenlist==1.4.1
+fsspec==2024.9.0
+future==1.0.0
+gitdb==4.0.11
+GitPython==3.1.43
+google-auth==2.34.0
+google-auth-oauthlib==0.4.6
+grpcio==1.66.1
+h5py==3.11.0
+idna==3.9
+image==1.5.32
+imageio==2.8.0
+Jinja2==3.1.4
+joblib==1.4.2
+kiwisolver==1.4.7
+lightning==2.4.0
+lightning-utilities==0.11.7
+Markdown==3.7
+MarkupSafe==2.1.5
+matplotlib==3.5.3
+mpmath==1.3.0
+multidict==6.1.0
+networkx==3.3
+numpy==1.23.3
+oauthlib==3.2.2
+opencv-contrib-python==4.6.0.66
+opencv-python==4.6.0.66
+packaging==24.1
+pandas==2.2.2
+pathtools==0.1.2
+pillow==10.4.0
+pip==21.2.3
+platformdirs==4.3.3
+promise==2.3
+protobuf==3.19.6
+psutil==6.0.0
+pyasn1==0.6.1
+pyasn1_modules==0.4.1
+pyDeprecate==0.3.1
+PyExifTool==0.1.1
+pyparsing==3.0.9
+python-dateutil==2.8.2
+pytorch-lightning==1.5.10
+pytz==2024.2
+PyWavelets==1.7.0
+PyYAML==6.0.2
+requests==2.32.3
+requests-oauthlib==2.0.0
+rsa==4.9
+scikit-image==0.19.2
+scikit-learn==1.0.2
+scipy==1.8.0
+seaborn==0.11.0
+sentry-sdk==2.14.0
+setproctitle==1.3.2
+setuptools==59.5.0
+shortuuid==1.0.13
+six==1.16.0
+smmap==5.0.0
+spectral==0.23
+sqlparse==0.5.1
+sympy==1.13.2
+tensorboard==2.10.0
+tensorboard-data-server==0.6.1
+tensorboard-plugin-wit==1.8.1
+threadpoolctl==3.5.0
+tifffile==2024.8.30
+torch==1.11.0+cpu
+torchaudio==0.11.0
+torchmetrics==0.9.3
+torchvision==0.12.0+cpu
+tornado==6.2
+tqdm==4.64.1
+typing_extensions==4.12.2
+tzdata==2024.1
+urllib3==1.26.12
+wandb==0.18.0
+Werkzeug==3.0.4
+wheel==0.44.0
+yarl==1.11.1

wandb/offline-run-20240916_141122-l9un9d3d/files/wandb-metadata.json

@@ -0,0 +1,45 @@
+{
+  "os": "Windows-10-10.0.22631-SP0",
+  "python": "3.10.0",
+  "startedAt": "2024-09-16T07:11:22.358661Z",
+  "args": [
+    "--data_path",
+    "D:\\College\\Project",
+    "--model",
+    "deephs_net",
+    "--fruit",
+    "mango",
+    "--classification_type",
+    "ripeness",
+    "--seed",
+    "23312323",
+    "--num_epochs",
+    "2"
+  ],
+  "program": "C:\\Users\\intha\\deephs_fruit\\classification\\train.py",
+  "codePath": "classification\\train.py",
+  "git": {
+    "remote": "https://github.com/hut22929/deephs_fruit.git",
+    "commit": "e74580eea097ac4af5f40b10344603c5fb7e93a3"
+  },
+  "root": "C:\\Users\\intha\\deephs_fruit",
+  "host": "Hut",
+  "username": "intha",
+  "executable": "C:\\Users\\intha\\deephs_fruit\\venv\\Scripts\\python.exe",
+  "codePathLocal": "classification\\train.py",
+  "cpu_count": 4,
+  "cpu_count_logical": 8,
+  "disk": {
+    "/": {
+      "total": "148813901824",
+      "used": "146011209728"
+    }
+  },
+  "memory": {
+    "total": "12674457600"
+  },
+  "cpu": {
+    "count": 4,
+    "countLogical": 8
+  }
+}

wandb/offline-run-20240916_141122-l9un9d3d/files/wandb-summary.json

@@ -0,0 +1 @@
+{}

wandb/offline-run-20240916_142954-6krtpvlu/files/config.yaml

@@ -0,0 +1,25 @@
+_wandb:
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+            "4": 3.10.0
+            "5": 0.18.0
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+            "13": windows-amd64