[py][db] Created a sample loader able to process eyes annotations

bob/bio/face/database/sample_loaders.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+
+"""  Sample loader"""
+
+
+from bob.bio.base.database import CSVToSampleLoader
+from bob.pipelines import Sample, DelayedSample, SampleSet
+import functools
+import os
+
+
+class CSVToSampleLoaderEyesAnnotations(CSVToSampleLoader):
+    """
+    Convert CSV files in the format below to either a list of
+    :any:`bob.pipelines.DelayedSample` or :any:`bob.pipelines.SampleSet`
+
+    Convert  leye_x, leye_y, reye_x, reye_y attributes to `annotations = (leye, reye)`
+
+    """
+
+    def convert_row_to_sample(self, row, header):
+        path = row[0]
+        subject = row[1]
+        kwargs = dict([[h, r] for h, r in zip(header[2:], row[2:])])
+
+        annotations = {
+            "leye": (kwargs["leye_x"], kwargs["leye_y"]),
+            "reye": (kwargs["reye_x"], kwargs["reye_y"]),
+        }
+
+        kwargs.pop("leye_x")
+        kwargs.pop("leye_y")
+        kwargs.pop("reye_x")
+        kwargs.pop("reye_y")
+
+        return DelayedSample(
+            functools.partial(
+                self.data_loader,
+                os.path.join(self.dataset_original_directory, path + self.extension),
+            ),
+            key=path,
+            subject=subject,
+            annotations=annotations,
+            **kwargs,
+        )
+
+
+"""
+class CSVToSampleLoaderEyesAnnotations(CSVToSampleLoader):
+    def __call__(self, filename):
+        import ipdb
+
+        ipdb.set_trace()
+        samples = super(CSVToSampleLoaderEyesAnnotations, self).__call__(filename)
+
+        def generate_annotations(sample):
+            
+            Convert  leye_x, leye_y, reye_x, reye_y attributes to
+            `annotations = (leye, reye)`
+
+            
+
+            check_keys = [
+                a in (sample.__dict__.keys())
+                for a in ["leye_x", "leye_y", "reye_x", "reye_y"]
+            ]
+
+            if not check_keys:
+                raise ValueError(
+                    "Sample needs to contain the following annotations: 'leye_x', 'leye_y', 'reye_x', 'reye_y'"
+                )
+
+            annotations = {
+                "leye": (sample.leye_x, sample.leye_y),
+                "reye": (sample.reye_x, sample.reye_y),
+            }
+
+            # Changing the state of samples for efficiency
+            # We might have a gigantic amount of datasets
+            sample.__dict__.pop("leye_x")
+            sample.__dict__.pop("leye_y")
+            sample.__dict__.pop("reye_x")
+            sample.__dict__.pop("reye_y")
+            sample.annotations = annotations
+
+        for sample in samples:
+            generate_annotations(sample)
+
+        return samples
+"""