Update README with Pytorch fix. Update poetry dependencies. Update scripts with package imports.

Author: ltindall

README.md

@@ -2,6 +2,7 @@
 
 This repo provides the pipeline for working with RF datasets, labeling them and training both IQ and spectrogram based models. The SigMF standard is used for managing RF data and the labels/annotations on the data. It also uses the Torchsig framework for performing RF related augmentation of the data to help make the trained models more robust and functional in the real world.
 
+
 ## Prerequisites
 
 ### Poetry
@@ -44,10 +45,23 @@ See [Poetry docs](https://python-poetry.org/docs/basic-usage/#activating-the-vir
 git clone https://github.com/IQTLabs/rfml-dev.git
 cd rfml-dev
 git submodule update --init --recursive
-poetry add ./torchsig
 poetry install
 ```
 
+## Verify install with GPU support (optional)
+
+```bash
+$ python -c 'import torch; print(torch.cuda.is_available())'
+True
+```
+
+If the output does not match or errors occur, try installing Pytorch manually ([current version](https://pytorch.org/get-started/locally/) or [previous versions](https://pytorch.org/get-started/previous-versions/)).
+#### Example
+
+```bash
+pip install torch==2.0.1 torchvision==0.15.2
+```
+
 
 # Building a model
 

label_scripts/label_bladerf_wifi.py

@@ -3,7 +3,7 @@
 from pathlib import Path
 from tqdm import tqdm
 
-import annotation_utils
+import rfml.annotation_utils as annotation_utils
 
 s3_data = {
     "anom_wifi": [

label_scripts/label_env.py

@@ -5,8 +5,8 @@
 import os
 import sys
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
-import annotation_utils
-import data as data_class
+import rfml.annotation_utils as annotation_utils
+import rfml.data as data_class
 
 
 

label_scripts/label_mavic.py

@@ -5,8 +5,8 @@
 import os
 import sys
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
-import annotation_utils
-import data as data_class
+import rfml.annotation_utils as annotation_utils
+import rfml.data as data_class
 
 
 

label_scripts/label_mini2.py

@@ -3,8 +3,8 @@
 from pathlib import Path
 from tqdm import tqdm
 
-import annotation_utils
-import data as data_class
+import rfml.annotation_utils as annotation_utils
+import rfml.data as data_class
 
 
 

label_scripts/label_nz_wifi.py

@@ -3,7 +3,7 @@
 from pathlib import Path
 from tqdm import tqdm
 
-import annotation_utils
+import rfml.annotation_utils as annotation_utils
 
 s3_data = {
     "anom_wifi": [

label_scripts/label_nz_wifi_multiprocessing.py

@@ -9,7 +9,7 @@
 from pathlib import Path
 from tqdm import tqdm
 
-import annotation_utils
+import rfml.annotation_utils as annotation_utils
 
 def worker_wrapper(fn, kwargs):
     def try_fn():

poetry.lock

@@ -1,12 +1,12 @@
 [tool.poetry]
-name = "rfml-dev"
+name = "rfml"
 version = "0.1.0"
 description = ""
 authors = ["Lucas Tindall <[email protected]>"]
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.10"
+python = ">=3.10, <3.12"
 scikit-image = "^0.22.0"
 matplotlib = "^3.8.3"
 numpy = "^1.26.4"
@@ -18,8 +18,10 @@ pillow = "^10.2.0"
 python-on-whales = "^0.69.0"
 sigmf = "^1.2.0"
 tqdm = "^4.66.4"
-cupy = "^13.2.0"
 torch-model-archiver = "^0.11.1"
+torchsig = {path = "torchsig"}
+cupy-cuda12x = "^13.2.0"
+ultralytics = "^8.2.79"
 
 
 [tool.poetry.group.dev.dependencies]

pyproject.toml

@@ -5,9 +5,9 @@
 from cupyx.scipy.signal import spectrogram as cupyx_spectrogram
 from cupyx.scipy.ndimage import gaussian_filter as cupyx_gaussian_filter
 
-from spectrogram import *
+from rfml.spectrogram import *
 
-import data as data_class
+import rfml.data as data_class
 import matplotlib.pyplot as plt
 import numpy as np
 

rfml/annotation_utils.py

@@ -21,9 +21,9 @@
 from python_on_whales import docker
 from tqdm import tqdm
 
-from auto_label import auto_label, auto_label_configs
-from zst_parse import parse_zst_filename
-from spectrogram import spectrogram, spectrogram_cmap
+from rfml.auto_label import auto_label, auto_label_configs
+from rfml.zst_parse import parse_zst_filename
+from rfml.spectrogram import spectrogram, spectrogram_cmap
 
 SIGMF_META_DEFAULT = {
     "global": {  # https://github.com/sigmf/SigMF/blob/sigmf-v1.x/sigmf-spec.md#global-object

rfml/data.py

@@ -1,8 +1,8 @@
 from pathlib import Path
 
-from experiment import * 
-from train_iq import *
-from train_spec import *
+from rfml.experiment import * 
+from rfml.train_iq import *
+from rfml.train_spec import *
 
 
 # Ensure that data directories have sigmf-meta files with annotations 

rfml/run_experiments.py

@@ -1,6 +1,6 @@
 # Tests and helper scripts for data.py
 
-from data import Data, labels_to_sigmf, yield_label_metadata
+from rfml.data import Data, labels_to_sigmf, yield_label_metadata
 
 
 def test_spectrogram_generation(filename):

rfml/test_data.py

@@ -1,7 +1,7 @@
 # I/Q model training script
 
 from argparse import ArgumentParser, BooleanOptionalAction
-from sigmf_pytorch_dataset import SigMFDataset
+from rfml.sigmf_pytorch_dataset import SigMFDataset
 from torchsig.utils.visualize import IQVisualizer, SpectrogramVisualizer, two_channel_to_complex
 from torchsig.utils.dataset import SignalDataset
 from torchsig.datasets.sig53 import Sig53
@@ -33,9 +33,8 @@
 import torchsig
 import torch
 import os
-from sigmf_db_dataset import SigMFDB
-from sigmf_pytorch_dataset import SigMFDataset
-from models import ExampleNetwork
+from rfml.sigmf_pytorch_dataset import SigMFDataset
+from rfml.models import ExampleNetwork
 
 from torchsig.transforms import (
     Compose,

rfml/train_iq.py

@@ -5,7 +5,7 @@
 import yaml
 from pathlib import Path
 from tqdm import tqdm
-from data import *
+from rfml.data import *
 import shutil