Merge pull request #219 from InnopolisUni/siz

Siz

config/datasets/detection/detection_rotten_fruits.yaml

@@ -17,6 +17,10 @@ test:
   source: https://api.blackhole.ai.innopolis.university/public-datasets/detection_rotten_fruits/test.zip
   target: /tmp/rotten_fruits/test
 
+infer:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/detection_rotten_fruits/test.zip
+  target: /tmp/rotten_fruits/infer
+
 num_workers: 8
 
 val_size: 0.2

config/datasets/detection/detection_siz.yaml

@@ -0,0 +1,21 @@
+_target_: innofw.core.integrations.ultralytics.datamodule.UltralyticsDataModuleAdapter
+channels_num: 3
+date_time: 13.01.2024
+description: Набор данных содержит фото гнилых и свежих фруктов
+image_size: 800
+infer:
+  source: /home/qazybek/SIZ_win_sum/images/test/
+markup_info: Набор данных содержит разметку bounding box, под формат детекции гнилых
+  фруктов.
+name: detection_siz
+names:
+- Person
+num_classes: 1
+num_workers: 8
+task:
+- image-detection
+test:
+  source: /home/qazybek/SIZ_win_sum
+train:
+  source: /home/qazybek/SIZ_win_sum
+val_size: 0.2

config/datasets/detection/ttpla.yaml

@@ -0,0 +1,34 @@
+task:
+  - image-detection
+
+name: TTPLA dataset
+description: Aerial images dataset on transmission towers and power lines
+markup_info: https://github.com/r3ab/ttpla_dataset?tab=readme-ov-file
+date_time: 19.11.2022
+
+_target_: innofw.core.integrations.ultralytics.datamodule.UltralyticsDataModuleAdapter
+
+train:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/TTPLA/train.zip
+  target: /tmp/TTPLA/train/
+
+test:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/TTPLA/test.zip
+  target: /tmp/TTPLA/test/
+
+infer:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/TTPLA/test.zip
+  target: /tmp/TTPLA/test/
+
+num_workers: 8
+
+val_size: 0.2
+channels_num: 3
+image_size: 3840
+num_classes: 5
+names:
+  - cable
+  - tower_lattice
+  - tower_tucohy
+  - tower_wooden
+  - void

config/datasets/detection_lep.yaml

@@ -11,13 +11,13 @@ _target_: innofw.core.integrations.ultralytics.datamodule.UltralyticsDataModuleA
 
 train:
   source: https://api.blackhole.ai.innopolis.university/public-datasets/testing/lep/train.zip
-  target: ./data/lep/
+  target: /tmp/data/lep/train
 test:
   source: https://api.blackhole.ai.innopolis.university/public-datasets/testing/lep/test.zip
-  target: ./data/lep/
+  target: /tmp/data/lep/test
 infer:
   source: https://api.blackhole.ai.innopolis.university/public-datasets/testing/lep/test.zip
-  target: ./data/lep/
+  target: /tmp/data/lep/infer
 
 num_workers: 8
 

config/datasets/detection_lep_insplad.yaml

@@ -0,0 +1,69 @@
+task:
+  - image-detection
+
+name: lep_insplad
+description: "InsPLAD A Dataset and Benchmark for Power Line Asset Inspection in UAV Images, Link: https://github.com/andreluizbvs/InsPLAD"
+
+markup_info: Yolo detection annotations of powerline elements
+date_time: 18.11.2022
+
+_target_: innofw.core.integrations.ultralytics.datamodule.UltralyticsDataModuleAdapter
+
+train:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/INSPLAD/train.zip
+  target: /tmp/INSPLAD/train
+test:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/INSPLAD/test.zip
+  target: /tmp/INSPLAD/test
+infer:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/INSPLAD/test.zip
+  target: /tmp/INSPLAD/test
+
+num_workers: 8
+
+val_size: 0.2
+channels_num: 3
+image_size: 600
+num_classes: 18
+names:
+  - yoke
+  - suspension
+  - spacer
+  - stockbridge_damper
+  - lightning_rod_shackle
+  - lightning_rod_suspension
+  - polymer
+  - glass_insulator
+  - tower_id_plate
+  - vari_grip
+  - polymer_insulator_lower_shackle
+  - polymer_insulator_upper_shackle
+  - polymer_insulator_tower_shackle
+  - glass_insulator_big_shackle
+  - glass_insulator_small_shackle
+  - glass_insulator_tower_shackle
+  - spiral_damper
+  - sphere
+
+#  Dataset structure is as follows:
+#  images/
+#    train/
+#      *.jpg
+#    test/
+#      *.jpg
+
+#  labels/
+#    train/
+#      *.txt
+#    test/
+#      *.txt
+
+#  Note that each archive consist only corresponding folders:
+#  train.zip/
+#    images/
+#      train/
+#        *.jpg
+#    labels/
+#      train/
+#        *.txt
+#  Similar for test.zip and infer.zip

config/datasets/semantic-segmentation/large_scale_fish.yaml

@@ -0,0 +1,15 @@
+_target_: innofw.core.datamodules.lightning_datamodules.semantic_segmentation.stroke_dm.DirSegmentationLightningDataModule
+date_time: 29.01.2024
+description: https://www.kaggle.com/datasets/crowww/a-large-scale-fish-dataset
+markup_info: binary segmentation masks
+name: Fish semantic segmentation dataset
+task:
+  - image-segmentation
+
+test:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/fish/test.zip
+  target: ./data/fish/test
+train:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/fish/train.zip
+  target: ./data/fish/train
+

config/datasets/semantic-segmentation/self_driving_dataset.yaml

@@ -0,0 +1,15 @@
+_target_: innofw.core.datamodules.lightning_datamodules.semantic_segmentation.stroke_dm.DirSegmentationLightningDataModule
+date_time: 29.01.2024
+description: https://www.kaggle.com/datasets/crowww/a-large-scale-fish-dataset
+markup_info: binary segmentation masks
+name: Fish semantic segmentation dataset
+task:
+  - image-segmentation
+
+test:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/driving/test.zip
+  target: ./data/fish/test
+train:
+  source: https://api.blackhole.ai.innopolis.university/public-datasets/driving/train.zip
+  target: ./data/fish/train
+

config/experiments/detection/IM_130124_gdsfjbjh2_siz.yaml

@@ -0,0 +1,13 @@
+# @package _global_
+accelerator: gpu
+batch_size: 32
+ckpt_path: /home/qazybek/pmi_tatneft/innofw/dui/logs/something/20240122-093931/weights/best.pt
+defaults:
+- override /datasets: detection/detection_siz.yaml
+- override /models: detection/yolov5.yaml
+devices: 1
+epochs: 3
+project: siz
+random_seed: 43
+task: image-detection
+weights_freq: 1

config/experiments/detection/IM_190722_gdsfjbjh2_yolov5_fruits.yaml

@@ -1,14 +1,10 @@
 # @package _global_
+batch_size: 2
 defaults:
-  - override /models: detection/yolov5
-  - override /datasets: detection/detection_rotten_fruits
-
-
-project: "rotten_fruits"
-task: "image-detection"
+- override /models: detection/yolov5
+- override /datasets: detection/detection_rotten_fruits
+epochs: 3
+project: rotten_fruits
 random_seed: 43
-epochs: 300
-batch_size: 2
+task: image-detection
 weights_freq: 1
-
-ckpt_path: /tmp/chkpt

config/experiments/detection/KA_120722_8adfcdaa_yolov5.yaml

@@ -1,12 +1,11 @@
 # @package _global_
+batch_size: 32
 defaults:
-  - override /models: detection/yolov5
-  - override /datasets: detection_lep
-  - override /optimizers: sgd
-
-project: "lep"
-task: "image-detection"
+- override /datasets: detection_lep
+- override /optimizers: sgd
+- override /models: detection/yolov5x.yaml
+epochs: 500
+project: lep
 random_seed: 42
-epochs: 2
-batch_size: 2
+task: image-detection
 weights_freq: 1

config/experiments/detection/KA_120722_8adfcdaa_yolov5_non_pretrained.yaml

@@ -1,15 +1,12 @@
 # @package _global_
+batch_size: 2
+ckpt_path: /home/qazybek/pmi_tatneft/innofw/dui/logs/something/20240122-082640/weights/best.pt
 defaults:
-  - override /models: detection/yolov5
-  - override /datasets: detection/lep
-  - override /initializations: random
-
-
-project: "lep"
-task: "image-detection"
+- override /models: detection/yolov5
+- override /datasets: detection_lep.yaml
+- override /initializations: random
+epochs: 5
+project: lep
 random_seed: 42
-epochs: 1
-batch_size: 2
+task: image-detection
 weights_freq: 1
-
-# ckpt_path: https://api.blackhole.ai.innopolis.university/pretrained/lep_yolov5.pt

config/experiments/detection/KG_190124_wpiig1_ttpla.yaml

@@ -0,0 +1,21 @@
+# @package _global_
+defaults:
+  - override /models: detection/yolov5
+  - override /datasets: detection/detection_ttpla
+  - override /optimizers: sgd
+
+project: "ttpla"
+task: "image-detection"
+random_seed: 42
+epochs: 20
+batch_size: 2
+weights_freq: 1
+accelerator: gpu
+devices: 1
+
+wandb:
+  enable: True
+  project: ttpla
+  entity: "k-galliamov"
+  group: none
+  job_type: training

config/experiments/detection/KG_210124_xpibms_insplad.yaml

@@ -0,0 +1,21 @@
+# @package _global_
+defaults:
+  - override /models: detection/yolov5
+  - override /datasets: detection_lep_insplad
+  - override /optimizers: sgd
+
+project: "ttpla"
+task: "image-detection"
+random_seed: 42
+epochs: 2
+batch_size: 2
+weights_freq: 1
+accelerator: gpu
+devices: 1
+
+wandb:
+  enable: True
+  project: ttpla
+  entity: "k-galliamov"
+  group: none
+  job_type: training

config/experiments/semantic-segmentation/AS_151123_oks.yaml

@@ -1,30 +1,24 @@
-# @package _global_
-defaults:
-  - override /models: semantic-segmentation/deeplabv3plus
-  - override /datasets: semantic-segmentation/oks_151123
-  - override /loggers: wandb
-  - override /losses: semantic-segmentation/dice
-  - override /optimizers: adam
-  - override /augmentations_train: linear-roads-bin-seg
-
+accelerator: gpu
+batch_size: 20
 datasets:
-  batch_size: 20
-  num_workers: 42
-
-
+- batch_size: 20
+- num_workers: 42
+defaults:
+- override /models: semantic-segmentation/deeplabv3plus
+- override /datasets: semantic-segmentation/oks_151123
+- override /loggers: wandb
+- override /losses: semantic-segmentation/dice
+- override /optimizers: adam
+- override /augmentations_train: linear-roads-bin-seg
+devices: 1
+epochs: 1
 models:
-  in_channels: 3
-  classes: 1
-  encoder_name: resnet101
-  encoder_depth: 5
-  decoder_channels: 256
-  encoder_weights:
-
+- in_channels: 3
+- classes: 1
+- encoder_name: resnet101
+- encoder_depth: 5
+- decoder_channels: 256
+num_workers: 42
 project: oks
-task: image-segmentation
 random_seed: 42
-accelerator: gpu
-devices: 1
-batch_size: 20
-num_workers: 42
-epochs: 40
+task: image-segmentation