diff --git a/bob/bio/face/database/ijbc.py b/bob/bio/face/database/ijbc.py
index d9428f7a4baac1ccb0108e7810290c2da159ad29..566695318a1ac96d94241aed96c9eca36596ee47 100644
--- a/bob/bio/face/database/ijbc.py
+++ b/bob/bio/face/database/ijbc.py
@@ -1,68 +1,147 @@
-#!/usr/bin/env python
-# vim: set fileencoding=utf-8 :
-# Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
-# Sat 20 Aug 15:43:10 CEST 2020
-
-from bob.pipelines.utils import hash_string
-from bob.extension.download import get_file, find_element_in_tarball
-import pickle
+from bob.bio.base.pipelines.vanilla_biometrics.abstract_classes import Database
+import pandas as pd
+from bob.pipelines.sample import DelayedSample, SampleSet
+from bob.extension import rc
import os
+import bob.io.image
+from functools import partial
-def load_ijbc_sample(original_path, extension=[".jpg", ".png"]):
- for e in extension:
- path = original_path + e
- if os.path.exists(path):
- return path
- else:
- return ""
+def load(path):
+ return bob.io.image.load(os.path.join(rc["bob.db.ijbc.directory"], path))
-class IJBCDatabase:
- def __init__(self, pkl_directory=None):
- self.annotation_type = "bounding-box"
- self.fixed_positions = None
- self.allow_scoring_with_all_biometric_references = False
- self.hash_fn = hash_string
- self.memory_demanding = True
+def _make_sample_from_template_row(row, image_directory):
+ return DelayedSample(
+ load=partial(
+ bob.io.image.load, path=os.path.join(image_directory, row["FILENAME"])
+ ),
+ template_id=str(row["TEMPLATE_ID"]),
+ subject_id=str(row["SUBJECT_ID"]),
+ key=os.path.splitext(row["FILENAME"])[0],
+ annotations={
+ "topleft": (float(row["FACE_Y"]), float(row["FACE_X"])),
+ "bottomright": (
+ float(row["FACE_Y"]) + float(row["FACE_HEIGHT"]),
+ float(row["FACE_X"]) + float(row["FACE_WIDTH"]),
+ ),
+ "size": (float(row["FACE_HEIGHT"]), float(row["FACE_WIDTH"])),
+ },
+ )
- if pkl_directory is None:
- urls = IJBCDatabase.urls()
- pkl_directory = get_file(
- "ijbc.tar.gz", urls, file_hash="4b25d7f10595eb9f97f328a2d448d957"
- )
- self.pkl_directory = pkl_directory
+def _make_sample_set_from_template_group(template_group, image_directory):
+ samples = list(
+ template_group.apply(
+ _make_sample_from_template_row, axis=1, image_directory=image_directory
+ )
+ )
+ return SampleSet(
+ samples, template_id=samples[0].template_id, subject_id=samples[0].subject_id
+ )
+
- def _assert_group(self, group):
- assert (
- group == "dev"
- ), "The IJBC database only has a `dev` group. Received : {}".format(group)
+class IJBCDatabase(Database):
+ def __init__(
+ self,
+ protocol="1:1",
+ original_directory=rc["bob.bio.face.ijbc.directory"],
+ **kwargs
+ ):
+ self._check_protocol(protocol)
- def references(self, group="dev"):
- self._assert_group(group)
- return pickle.loads(
- find_element_in_tarball(self.pkl_directory, "db_references.pickle", True)
+ super().__init__(
+ name="ijbc",
+ protocol=protocol,
+ allow_scoring_with_all_biometric_references=False,
+ annotation_type="eyes-center",
+ fixed_positions=None,
+ memory_demanding=True,
)
- def probes(self, group="dev"):
- self._assert_group(group)
- return pickle.loads(
- find_element_in_tarball(self.pkl_directory, "db_probes.pickle", True)
+ self.image_directory = os.path.join(original_directory, "images")
+ self.protocol_directory = os.path.join(original_directory, "protocols")
+ self._cached_probes = None
+ self._cached_references = None
+
+ self._load_metadata()
+
+ def _load_metadata(self):
+ # Load CSV files
+ self.reference_templates = pd.concat(
+ [
+ pd.read_csv(
+ os.path.join(self.protocol_directory, "ijbc_1N_gallery_G1.csv")
+ ),
+ pd.read_csv(
+ os.path.join(self.protocol_directory, "ijbc_1N_gallery_G2.csv")
+ ),
+ ]
+ )
+
+ self.probe_templates = pd.read_csv(
+ os.path.join(self.protocol_directory, "ijbc_1N_probe_mixed.csv")
+ )
+
+ self.matches = pd.read_csv(
+ os.path.join(self.protocol_directory, "ijbc_11_G1_G2_matches.csv"),
+ names=["REFERENCE_TEMPLATE_ID", "PROBE_TEMPLATE_ID"],
)
def background_model_samples(self):
- import cloudpickle
+ return None
- return cloudpickle.loads(
- find_element_in_tarball(
- self.pkl_directory, "db_background_model_samples.pickle", True
+ def probes(self, group="dev"):
+ self._check_group(group)
+ if self._cached_probes is None:
+ self._cached_probes = list(
+ self.probe_templates.groupby("TEMPLATE_ID").apply(
+ _make_sample_set_from_template_group,
+ image_directory=self.image_directory,
+ )
)
+
+ # Link probes to the references they have to be compared with
+ # We might make that faster if we manage to write it as a Panda instruction
+ grouped_matches = self.matches.groupby("PROBE_TEMPLATE_ID")
+ for probe_sampleset in self._cached_probes:
+ probe_sampleset.references = list(
+ grouped_matches.get_group(int(probe_sampleset.template_id))[
+ "REFERENCE_TEMPLATE_ID"
+ ]
+ )
+
+ return self._cached_probes
+
+ def references(self, group="dev"):
+ self._check_group(group)
+ if self._cached_references is None:
+ self._cached_references = list(
+ self.reference_templates.groupby("TEMPLATE_ID").apply(
+ _make_sample_set_from_template_group,
+ image_directory=self.image_directory,
+ )
+ )
+
+ return self._cached_references
+
+ def all_samples(self, group="dev"):
+ self._check_group(group)
+
+ return self.references() + self.probes()
+
+ def groups(self):
+ return ["dev"]
+
+ def protocols(self):
+ return ["1:1"]
+
+ def _check_protocol(self, protocol):
+ assert protocol in self.protocols(), "Unvalid protocol `{}` not in {}".format(
+ protocol, self.protocols()
)
- @staticmethod
- def urls():
- return [
- "https://www.idiap.ch/software/bob/databases/latest/ijbc.tar.gz",
- "http://www.idiap.ch/software/bob/databases/latest/ijbc.tar.gz",
- ]
+ def _check_group(self, group):
+ assert group in self.groups(), "Unvalid group `{}` not in {}".format(
+ group, self.groups()
+ )