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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Comparing 2 samples\n",
+ "\n",
+ "In this example we show how to take a baseline and compare two samples with it"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "WARNING:tensorflow:SavedModel saved prior to TF 2.4 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), *NOT* tf.saved_model.save(). To confirm, there should be a file named \"keras_metadata.pb\" in the SavedModel directory.\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-0._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-1._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-2._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-3._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-3._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-4._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-6._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-5._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-6._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-7._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-8._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-9._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-10._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-11._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-12._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-13._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-14._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-15._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-16._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-17._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-18._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-19._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-20._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-21._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-22._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-23._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-24._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-25._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-26._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-27._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-28._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-29._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-30._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-31._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-32._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-33._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-34._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-35._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-36._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-37._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-38._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-39._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-40._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-41._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-42._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-43._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-44._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-45._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-46._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-47._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-48._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-51._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-52._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-49._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-50._inbound_nodes\n",
+ "WARNING:tensorflow:A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.\n",
+ "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n",
+ "-0.40941279115199114\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Add the path of sample A with sample B\n",
+ "SAMPLE_A = \"\"\n",
+ "SAMPLE_B = \"\"\n",
+ "\n",
+ "from bob.pipelines import SampleSet, DelayedSample\n",
+ "import bob.io.base\n",
+ "import functools\n",
+ "\n",
+ "# Picking a baseline\n",
+ "from bob.bio.face.embeddings.tensorflow import inception_resnet_v2_casia_centerloss_2018\n",
+ "\n",
+ "# Setting where the eyes are for each sample (here the two samples have the same eyes position)\n",
+ "fixed_positions = {\"leye\":(60,123), \"reye\":(60,63)}\n",
+ "\n",
+ "pipeline = inception_resnet_v2_casia_centerloss_2018(\n",
+ " annotation_type=\"eyes-center\", fixed_positions=fixed_positions\n",
+ ")\n",
+ "\n",
+ "def create_sample(path, key):\n",
+ " return SampleSet(\n",
+ " [DelayedSample(functools.partial(bob.io.base.load, path), key=str(key))],\n",
+ " key=str(key),\n",
+ " biometric_id=str(key),)\n",
+ "\n",
+ "sample_A = create_sample(SAMPLE_A, 0)\n",
+ "sample_B = create_sample(SAMPLE_B, 1)\n",
+ "\n",
+ "\n",
+ "biometric_references = pipeline.create_biometric_reference([sample_A])\n",
+ "scores, _ = pipeline.compute_scores([sample_B], biometric_references)\n",
+ "\n",
+ "# Printing the score from the first sample\n",
+ "print(scores[0].samples[0].data)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Extracting embeddings from two samples"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "WARNING:tensorflow:SavedModel saved prior to TF 2.4 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), *NOT* tf.saved_model.save(). To confirm, there should be a file named \"keras_metadata.pb\" in the SavedModel directory.\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-0._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-1._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-2._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-3._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-3._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-4._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-6._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-5._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-6._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-7._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-8._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-9._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-10._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-11._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-12._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-13._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-14._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-15._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-16._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-17._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-18._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-19._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-20._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-21._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-22._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-23._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-24._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-25._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-26._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-27._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-28._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-29._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-30._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-31._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-32._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-33._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-34._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-35._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-36._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-37._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-38._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-39._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-40._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-41._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-42._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-43._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-44._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-45._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-46._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-47._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-48._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-51._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer-52._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-49._inbound_nodes\n",
+ "WARNING:tensorflow:Unresolved object in checkpoint: (root).layer_with_weights-50._inbound_nodes\n",
+ "WARNING:tensorflow:A checkpoint was restored (e.g. tf.train.Checkpoint.restore or tf.keras.Model.load_weights) but not all checkpointed values were used. See above for specific issues. Use expect_partial() on the load status object, e.g. tf.train.Checkpoint.restore(...).expect_partial(), to silence these warnings, or use assert_consumed() to make the check explicit. See https://www.tensorflow.org/guide/checkpoint#loading_mechanics for details.\n",
+ "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n",
+ "WARNING:tensorflow:5 out of the last 8 calls to <function Model.make_predict_function.<locals>.predict_function at 0x7fe46e4b54d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n",
+ "[array([ 0.09172679, 0.0324957 , 0.03359955, -0.00483591, 0.02353592,\n",
+ " 0.04886897, -0.00094087, 0.06978928, 0.10372686, -0.10392421,\n",
+ " 0.13330463, 0.07076985, 0.08029327, -0.04671128, -0.02518994,\n",
+ " 0.12051351, 0.06940517, -0.038332 , -0.02331832, 0.02664019,\n",
+ " 0.04434336, -0.02471577, -0.0102796 , -0.085636 , 0.09365616,\n",
+ " 0.01478034, -0.01528178, 0.03954509, 0.02043953, 0.0704874 ,\n",
+ " -0.03089085, 0.0312874 , 0.10803461, -0.05972857, -0.16184652,\n",
+ " -0.03643044, 0.09576611, -0.08911359, -0.13417085, -0.03623924,\n",
+ " 0.16680372, 0.06437656, -0.12195335, 0.15070474, -0.00109789,\n",
+ " -0.01936167, 0.12604736, -0.02172692, -0.16884778, -0.03880082,\n",
+ " 0.03399109, -0.05475918, 0.0058937 , -0.24445663, -0.0814684 ,\n",
+ " 0.06544494, 0.09598684, 0.18717638, 0.02309373, -0.1937956 ,\n",
+ " -0.11580025, -0.03947522, 0.02225816, -0.17796317, 0.0286997 ,\n",
+ " 0.05637549, 0.13862395, 0.07888459, -0.0746187 , -0.06245924,\n",
+ " -0.05905129, -0.06469788, -0.13217713, -0.00836692, -0.03132226,\n",
+ " 0.02515431, 0.10684554, 0.03239268, -0.08999073, 0.09488151,\n",
+ " 0.07205841, -0.05697955, -0.01520361, -0.10826666, -0.11681797,\n",
+ " -0.06068925, 0.08056987, 0.11805228, -0.01560696, -0.05713017,\n",
+ " 0.00941482, -0.08339076, 0.10243417, 0.1385035 , -0.08926324,\n",
+ " -0.08198499, 0.09009691, 0.01847403, -0.04287886, 0.01292743,\n",
+ " -0.02277992, -0.14719044, 0.10625618, 0.00111244, 0.19167267,\n",
+ " -0.01272508, 0.08188605, -0.12089421, -0.05653883, -0.05532645,\n",
+ " -0.05844725, -0.11874794, 0.12547068, -0.06742927, -0.07416619,\n",
+ " -0.01912123, 0.04917778, -0.10811004, 0.04180698, 0.18301588,\n",
+ " -0.00808303, 0.00328449, -0.12431399, -0.0101751 , -0.10478832,\n",
+ " 0.12978972, 0.09860662, 0.12227818], dtype=float32)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Add the path of sample A with sample B\n",
+ "SAMPLE_A = \"\"\n",
+ "SAMPLE_B = \"\"\n",
+ "\n",
+ "from bob.pipelines import SampleSet, DelayedSample\n",
+ "import bob.io.base\n",
+ "import functools\n",
+ "\n",
+ "# Picking a baseline\n",
+ "from bob.bio.face.embeddings.tensorflow import inception_resnet_v2_casia_centerloss_2018\n",
+ "\n",
+ "# Setting where the eyes are for each sample (here the two samples have the same eyes position)\n",
+ "fixed_positions = {\"leye\":(60,123), \"reye\":(60,63)}\n",
+ "\n",
+ "pipeline = inception_resnet_v2_casia_centerloss_2018(\n",
+ " annotation_type=\"eyes-center\", fixed_positions=fixed_positions\n",
+ ")\n",
+ "transformer = pipeline.transformer\n",
+ "\n",
+ "def create_sample(path, key):\n",
+ " return SampleSet(\n",
+ " [DelayedSample(functools.partial(bob.io.base.load, path), key=str(key))],\n",
+ " key=str(key),\n",
+ " biometric_id=str(key),)\n",
+ "\n",
+ "sample_A = create_sample(SAMPLE_A, 0)\n",
+ "sample_B = create_sample(SAMPLE_B, 1)\n",
+ "\n",
+ "\n",
+ "transformed_samples = transformer.transform([sample_A, sample_B])\n",
+ "\n",
+ "print([x.data for x in transformed_samples[0].samples])\n",
+ "\n",
+ "\n",
+ "#biometric_references = pipeline.create_biometric_reference([sample_A])\n",
+ "#scores, _ = pipeline.compute_scores([sample_B], biometric_references)\n",
+ "\n",
+ "# Printing the score from the first sample\n",
+ "#print(scores[0].samples[0].data)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}