kurzti88066/Fahrsimulator_MSY2526_AI
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weigmi87303
2026-01-27 19:10:24 +01:00
parent eee173dc0b
commit 9951d8b4f9
4 changed files with 748 additions and 35 deletions
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model_training/DeepSVDD/deepSVDD.ipynb
+25 -12
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@@ -107,7 +107,8 @@
"metadata": {},
"outputs": [],
"source": [
"dataset_path = Path(r\"data-paulusjafahrsimulator-gpu/new_datasets/combined_dataset_25hz.parquet\")"
"dataset_path = Path(r\"data-paulusjafahrsimulator-gpu/new_datasets/combined_dataset_25hz.parquet\")\n",
"# dataset_path = Path(r\"/home/jovyan/data-paulusjafahrsimulator-gpu/new_datasets/120s_combined_dataset_25hz.parquet\")"
]
},
{
@@ -475,7 +476,7 @@
"metadata": {},
"outputs": [],
"source": [
"normalizer_path=Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/normalizer.pkl')"
"normalizer_path=Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/normalizer_min_max_global.pkl')"
]
},
{
@@ -494,7 +495,7 @@
"print(len(eye_cols))\n",
"all_signal_columns = face_au_cols+eye_cols\n",
"print(len(all_signal_columns))\n",
"normalizer = fit_normalizer(train_df, all_signal_columns, method='standard', scope='subject')\n",
"normalizer = fit_normalizer(train_df, all_signal_columns, method='minmax', scope='global')\n",
"save_normalizer(normalizer, normalizer_path )"
]
},
@@ -691,10 +692,10 @@
"model = build_intermediate_fusion_autoencoder(\n",
" input_dim_mod1=len(face_au_cols),\n",
" input_dim_mod2=len(eye_cols),\n",
" encoder_hidden_dim_mod1=15, # individuell\n",
" encoder_hidden_dim_mod2=10, # individuell\n",
" latent_dim=8,\n",
" dropout_rate=0.3, # einstellbar\n",
" encoder_hidden_dim_mod1=12, # individuell\n",
" encoder_hidden_dim_mod2=8, # individuell\n",
" latent_dim=4,\n",
" dropout_rate=0.7, # einstellbar\n",
" neg_slope=0.1,\n",
" weight_decay=1e-3\n",
")\n",
@@ -708,7 +709,7 @@
" \"recon_modality_1\": 1.0,\n",
" \"recon_modality_2\": 1.0,\n",
" },\n",
" optimizer=tf.keras.optimizers.Adam(1e-2)\n",
" optimizer=tf.keras.optimizers.Adam(1e-3)\n",
" \n",
")\n",
"\n",
@@ -739,7 +740,7 @@
" \"recon_modality_1\": 1.0,\n",
" \"recon_modality_2\": 1.0,\n",
" },\n",
" optimizer=tf.keras.optimizers.Adam(1e-5),\n",
" optimizer=tf.keras.optimizers.Adam(1e-4),\n",
")\n",
"model.fit(\n",
" x=[X_face, X_eye],\n",
@@ -779,7 +780,7 @@
"metadata": {},
"outputs": [],
"source": [
"encoder_save_path =Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/encoder_6_deep.keras')\n",
"encoder_save_path =Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/encoder_8_deep.keras')\n",
"encoder.save(encoder_save_path)"
]
},
@@ -943,7 +944,7 @@
" return get_radius_from_arrays(nu, X_face, X_eye)\n",
"\n",
"\n",
"nu = 0.05\n",
"nu = 0.25\n",
"\n",
"train_dataset = tf.data.Dataset.from_tensor_slices((X_face, X_eye)).shuffle(64).batch(64)\n",
"# train_dataset = tf.data.Dataset.from_tensor_slices((X_face, X_eye))\n",
@@ -1018,7 +1019,7 @@
"metadata": {},
"outputs": [],
"source": [
"deep_svdd_save_path =Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/deep_svdd_05.keras')\n",
"deep_svdd_save_path =Path('data-paulusjafahrsimulator-gpu/saved_models/deepsvdd_save/deep_svdd_06.keras')\n",
"deep_svdd_net.save(deep_svdd_save_path)"
]
},
@@ -1075,6 +1076,18 @@
"test_predictions = (test_scores > 0).astype(int)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "575dddcf",
"metadata": {},
"outputs": [],
"source": [
"normal_acc = np.mean(test_predictions[y_test == 0] == 0)\n",
"anomaly_acc = np.mean(test_predictions[y_test == 1] == 1)\n",
"print(f'Accuracy on Test set: {accuracy_score(y_test, test_predictions)}')"
]
},
{
"cell_type": "code",
"execution_count": null,