diff --git a/README.md b/README.md index daaf870..0a03ba8 100644 --- a/README.md +++ b/README.md @@ -25,10 +25,17 @@ - `superclustering/regression_v1.onnx`: DNN for supercluster energy regression. Input format : `batch x 8 (features)`. Output : `batch x 1` (supercluster regressed energy). Used in `RecoHGCal/TICL/plugins/EGammaSuperclusterProducer.cc`. - `ticlv5/onnx_models/`: The models are trained based on TICLv5 reconstruction information using a simple CNN-based approach. Two models have been trained separately: one for trackster energy regression and one for particle ID. These models are saved in ONNX format for time optimization. - `Common input tensor`: Both models share the same initial input tensor, dimensions batch x 50 (layers) x 10 (clusters) x 3 (features). - - `ticlv5/patternrecognition/id_v*.onnx`: + - `ticlv5/DNN/patternrecognition/id_v*.onnx`: - `"input"`: Input tensor with dimensions batch x 50 (layers) x 10 (clusters) x 3 (features). - `"output/pid_output"`: Output tensor with dimensions batch x 8 representing particle ID probabilities (from a softmax output). The probabilities refer to: photon, electron, muon, neutral pion, charged hadron(pion), neutral hadron(kaon), ambiguous, and unknown cases (in that order). The probabilities help in classifying the particle based on its type, distinguishing between hadronic and electromagnetic categories. - - `ticlv5/linking/energy_v*.onnx`: + - `ticlv5/DNN/linking/energy_v*.onnx`: - `"input"`: Input tensor with dimensions batch x 50 (layers) x 10 (clusters) x 3 (features), concatenated with the output of the particle ID model ("output/pid_output"). - `"output/enreg_output"`: Output Tensor with dimension batch x 1 (regressed energy). This value represents the trackster energy as estimated by the model based on the training data, compared to the true and reconstructed energies of the particle. - +- `Common input tensor`: Both models share the same initial input tensor, dimensions batch x 50 (layers) x 10 (clusters) x 7 (features). + - The PFN models are designed to be trained on both low-level variables, such as layer cluster features, and high-level variables, such as trackster features. + - `ticlv5/PFN/patternrecognition/id_v*.onnx`: + - `"input"`: Input tensor with dimensions batch x 50 (layers) x 10 (clusters) x 7 (features). + - `"output/pid_output"`: Output tensor with dimensions batch x 8 representing particle ID probabilities (from a softmax output). The probabilities refer to: photon, electron, muon, neutral pion, charged hadron(pion), neutral hadron(kaon), ambiguous, and unknown cases (in that order). The probabilities help in classifying the particle based on its type, distinguishing between hadronic and electromagnetic categories. + - `ticlv5/PFN/linking/energy_v*.onnx`: + - `"input"`: Input tensor with dimensions batch x 50 (layers) x 10 (clusters) x 7 (features), concatenated with the output of the particle ID model ("output/pid_output"). + - `"output/enreg_output"`: Output Tensor with dimension batch x 1 (regressed energy). This value represents the trackster energy as estimated by the model based on the training data, compared to the true and reconstructed energies of the particle. diff --git a/ticlv5/onnx_models/linking/energy_v0.onnx b/ticlv5/onnx_models/DNN/linking/energy_v0.onnx similarity index 100% rename from ticlv5/onnx_models/linking/energy_v0.onnx rename to ticlv5/onnx_models/DNN/linking/energy_v0.onnx diff --git a/ticlv5/onnx_models/linking/id_v0.onnx b/ticlv5/onnx_models/DNN/linking/id_v0.onnx similarity index 100% rename from ticlv5/onnx_models/linking/id_v0.onnx rename to ticlv5/onnx_models/DNN/linking/id_v0.onnx diff --git a/ticlv5/onnx_models/patternrecognition/energy_v0.onnx b/ticlv5/onnx_models/DNN/patternrecognition/energy_v0.onnx similarity index 100% rename from ticlv5/onnx_models/patternrecognition/energy_v0.onnx rename to ticlv5/onnx_models/DNN/patternrecognition/energy_v0.onnx diff --git a/ticlv5/onnx_models/patternrecognition/id_v0.onnx b/ticlv5/onnx_models/DNN/patternrecognition/id_v0.onnx similarity index 100% rename from ticlv5/onnx_models/patternrecognition/id_v0.onnx rename to ticlv5/onnx_models/DNN/patternrecognition/id_v0.onnx diff --git a/ticlv5/onnx_models/PFN/linking/energy_v0.onnx b/ticlv5/onnx_models/PFN/linking/energy_v0.onnx new file mode 100644 index 0000000..f3ef699 Binary files /dev/null and b/ticlv5/onnx_models/PFN/linking/energy_v0.onnx differ diff --git a/ticlv5/onnx_models/PFN/linking/id_v0.onnx b/ticlv5/onnx_models/PFN/linking/id_v0.onnx new file mode 100644 index 0000000..51d1b2f Binary files /dev/null and b/ticlv5/onnx_models/PFN/linking/id_v0.onnx differ diff --git a/ticlv5/onnx_models/PFN/patternrecognition/energy_v0.onnx b/ticlv5/onnx_models/PFN/patternrecognition/energy_v0.onnx new file mode 100644 index 0000000..f3ef699 Binary files /dev/null and b/ticlv5/onnx_models/PFN/patternrecognition/energy_v0.onnx differ diff --git a/ticlv5/onnx_models/PFN/patternrecognition/id_v0.onnx b/ticlv5/onnx_models/PFN/patternrecognition/id_v0.onnx new file mode 100644 index 0000000..9ed0626 Binary files /dev/null and b/ticlv5/onnx_models/PFN/patternrecognition/id_v0.onnx differ