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Fix missing imageio dependency for BYOL notebooks #170

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645f59a
Fix hardcoded absolute paths in BYOL/Inference scripts using os.path.…
Vikasboura Mar 6, 2026
5229830
Fix incorrect _file_ usage and replace with __file__
Vikasboura Mar 6, 2026
0d9d660
Fix missing imageio dependency for BYOL notebooks
Vikasboura Mar 6, 2026
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9 changes: 9 additions & 0 deletions Deeplens_Self_Supervised_Learning_Yashwardhan_Deshmukh/requirements.txt
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Original file line number Diff line number Diff line change
@@ -0,0 +1,9 @@
tensorflow>=2.10.0
keras>=2.10.0
numpy>=1.21.0
pandas>=1.3.0
matplotlib>=3.5.0
pillow>=9.0.0
scikit-learn>=1.0.0
tqdm>=4.62.0
imageio>=2.19.0
6 changes: 5 additions & 1 deletion Transformers_Classification_DeepLense_Kartik_Sachdev/finetune.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import os
import torch
import torch.nn as nn
import torch.optim as optim
Expand All @@ -12,7 +13,10 @@
# Set device
device = "cuda" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
learning_method = "contrastive_embedding"
saved_model_path = "/home/kartik/git/deepLense_transformer_ssl/output/pretrained_contrastive_embedding.pth"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
saved_model_path = os.path.join(BASE_DIR, "output", "pretrained_contrastive_embedding.pth")

# Set hyperparameters
batch_size = 128
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12 changes: 11 additions & 1 deletion Transformers_Classification_DeepLense_Kartik_Sachdev/finetune_byol.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import os
import torch
import torch.nn as nn
import torch.optim as optim
Expand All @@ -21,7 +22,16 @@
# Set device
device = "cuda" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
learning_method = "contrastive_embedding"
saved_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-23-13-30-24/checkpoint/Resnet_finetune_Model_II_2023-07-23-13-30-24.pt"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
saved_model_path = os.path.join(
BASE_DIR,
"logger",
"2023-07-23-13-30-24",
"checkpoint",
"Resnet_finetune_Model_II_2023-07-23-13-30-24.pt"
)

# Set hyperparameters
batch_size = 512
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17 changes: 14 additions & 3 deletions Transformers_Classification_DeepLense_Kartik_Sachdev/inference.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
from __future__ import print_function

import os
from turtle import down

from utils.dataset import DefaultDatasetSetupSSL
Expand All @@ -19,8 +19,19 @@ def main():
labels_map = {0: "axion", 1: "cdm", 2: "no_sub"}
image_size = 224
channels = 1
log_dir = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-23-13-30-24"
finetune_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-23-13-30-24/checkpoint/Resnet_finetune_Model_II.pt"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))

# Use relative paths instead of hardcoded absolute paths
log_dir = os.path.join(BASE_DIR, "logger", "2023-07-23-13-30-24")
finetune_model_path = os.path.join(
BASE_DIR,
"logger",
"2023-07-23-13-30-24",
"checkpoint",
"Resnet_finetune_Model_II.pt"
)
batch_size = 512
num_workers = 8

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28 changes: 26 additions & 2 deletions ...rs_Classification_DeepLense_Kartik_Sachdev/self_supervised/examples/byol/finetune_byol.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import os
import torch
import torch.nn as nn
import torch.optim as optim
Expand Down Expand Up @@ -106,8 +107,31 @@ def get_transfomer_finetuned(saved_model_path, device, num_classes) -> nn.Module
def main():
# Set device
device = "cuda" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
pretrained_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-25-06-27-13/checkpoint/CrossFormer_pretrained_Model_II_2023-07-25-06-27-13.pt"
finetuned_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-25-06-27-13/checkpoint/CrossFormer_finetuned_Model_II_2023-07-25-06-27-13.pt"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))

# Use relative paths instead of hardcoded absolute paths
pretrained_model_path = os.path.join(
BASE_DIR,
"..",
"..",
"..",
"logger",
"2023-07-25-06-27-13",
"checkpoint",
"CrossFormer_pretrained_Model_II_2023-07-25-06-27-13.pt"
)
finetuned_model_path = os.path.join(
BASE_DIR,
"..",
"..",
"..",
"logger",
"2023-07-25-06-27-13",
"checkpoint",
"CrossFormer_finetuned_Model_II_2023-07-25-06-27-13.pt"
)

# Set hyperparameters
batch_size = 512
Expand Down
19 changes: 17 additions & 2 deletions ...s_Classification_DeepLense_Kartik_Sachdev/self_supervised/examples/byol/inference_byol.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
from __future__ import print_function
import os

from turtle import down

Expand Down Expand Up @@ -107,8 +108,22 @@ def main():
labels_map = {0: "axion", 1: "cdm", 2: "no_sub"}
image_size = 224
channels = 1
log_dir = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-25-06-27-13"
finetune_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-25-06-27-13/checkpoint/CrossFormer_finetuned_Model_II_2023-07-25-06-27-13.pt"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))

# Use relative paths instead of hardcoded absolute paths
log_dir = os.path.join(BASE_DIR, "..", "..", "..", "logger", "2023-07-25-06-27-13")
finetune_model_path = os.path.join(
BASE_DIR,
"..",
"..",
"..",
"logger",
"2023-07-25-06-27-13",
"checkpoint",
"CrossFormer_finetuned_Model_II_2023-07-25-06-27-13.pt"
)
batch_size = 512
num_workers = 8

Expand Down
26 changes: 24 additions & 2 deletions ...sification_DeepLense_Kartik_Sachdev/self_supervised/examples/byol/load_pretrained_byol.py
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Open in desktop
Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import os
import torch
import torch.nn as nn
import torch.optim as optim
Expand All @@ -21,8 +22,29 @@
# Set device
device = "cuda" # torch.device("cuda" if torch.cuda.is_available() else "cpu")
learning_method = "contrastive_embedding"
pretrained_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-23-13-30-24/checkpoint/Resnet_finetune_Model_II_2023-07-23-13-30-24.pt"
finetuned_model_path = "/home/kartik/git/DeepLense/Transformers_Classification_DeepLense_Kartik_Sachdev/logger/2023-07-23-13-30-24/checkpoint/Resnet_finetune_Model_II.pt"

# Define base directory relative to script location
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
pretrained_model_path = os.path.join(
BASE_DIR,
"..",
"..",
"..",
"logger",
"2023-07-23-13-30-24",
"checkpoint",
"Resnet_finetune_Model_II_2023-07-23-13-30-24.pt"
)
finetuned_model_path = os.path.join(
BASE_DIR,
"..",
"..",
"..",
"logger",
"2023-07-23-13-30-24",
"checkpoint",
"Resnet_finetune_Model_II.pt"
)

# Set hyperparameters
batch_size = 512
Expand Down