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import os
import glob
import pickle
import numpy as np
import h5py
from .base_dumper import BaseDumper
import sys
ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../"))
sys.path.insert(0, ROOT_DIR)
import utils
class yfcc(BaseDumper):
def get_seqs(self):
data_dir = os.path.join(self.config["rawdata_dir"], "yfcc100m")
for seq in self.config["data_seq"]:
for split in self.config["data_split"]:
split_dir = os.path.join(data_dir, seq, split)
dump_dir = os.path.join(self.config["feature_dump_dir"], seq, split)
cur_img_seq = glob.glob(os.path.join(split_dir, "images", "*.jpg"))
cur_dump_seq = [
os.path.join(dump_dir, path.split("/")[-1])
+ "_"
+ self.config["extractor"]["name"]
+ "_"
+ str(self.config["extractor"]["num_kpt"])
+ ".hdf5"
for path in cur_img_seq
]
self.img_seq += cur_img_seq
self.dump_seq += cur_dump_seq
def format_dump_folder(self):
if not os.path.exists(self.config["feature_dump_dir"]):
os.mkdir(self.config["feature_dump_dir"])
for seq in self.config["data_seq"]:
seq_dir = os.path.join(self.config["feature_dump_dir"], seq)
if not os.path.exists(seq_dir):
os.mkdir(seq_dir)
for split in self.config["data_split"]:
split_dir = os.path.join(seq_dir, split)
if not os.path.exists(split_dir):
os.mkdir(split_dir)
def format_dump_data(self):
print("Formatting data...")
pair_path = os.path.join(self.config["rawdata_dir"], "pairs")
self.data = {
"K1": [],
"K2": [],
"R": [],
"T": [],
"e": [],
"f": [],
"fea_path1": [],
"fea_path2": [],
"img_path1": [],
"img_path2": [],
}
for seq in self.config["data_seq"]:
pair_name = os.path.join(pair_path, seq + "-te-1000-pairs.pkl")
with open(pair_name, "rb") as f:
pairs = pickle.load(f)
# generate id list
seq_dir = os.path.join(self.config["rawdata_dir"], "yfcc100m", seq, "test")
name_list = np.loadtxt(os.path.join(seq_dir, "images.txt"), dtype=str)
cam_name_list = np.loadtxt(
os.path.join(seq_dir, "calibration.txt"), dtype=str
)
for cur_pair in pairs:
index1, index2 = cur_pair[0], cur_pair[1]
cam1, cam2 = h5py.File(
os.path.join(seq_dir, cam_name_list[index1]), "r"
), h5py.File(os.path.join(seq_dir, cam_name_list[index2]), "r")
K1, K2 = cam1["K"][()], cam2["K"][()]
[w1, h1], [w2, h2] = cam1["imsize"][()][0], cam2["imsize"][()][0]
cx1, cy1, cx2, cy2 = (
(w1 - 1.0) * 0.5,
(h1 - 1.0) * 0.5,
(w2 - 1.0) * 0.5,
(h2 - 1.0) * 0.5,
)
K1[0, 2], K1[1, 2], K2[0, 2], K2[1, 2] = cx1, cy1, cx2, cy2
R1, R2, t1, t2 = (
cam1["R"][()],
cam2["R"][()],
cam1["T"][()].reshape([3, 1]),
cam2["T"][()].reshape([3, 1]),
)
dR = np.dot(R2, R1.T)
dt = t2 - np.dot(dR, t1)
dt /= np.sqrt(np.sum(dt**2))
e_gt_unnorm = np.reshape(
np.matmul(
np.reshape(
utils.evaluation_utils.np_skew_symmetric(
dt.astype("float64").reshape(1, 3)
),
(3, 3),
),
np.reshape(dR.astype("float64"), (3, 3)),
),
(3, 3),
)
e_gt = e_gt_unnorm / np.linalg.norm(e_gt_unnorm)
f_gt_unnorm = np.linalg.inv(K2.T) @ e_gt @ np.linalg.inv(K1)
f_gt = f_gt_unnorm / np.linalg.norm(f_gt_unnorm)
self.data["K1"].append(K1), self.data["K2"].append(K2)
self.data["R"].append(dR), self.data["T"].append(dt)
self.data["e"].append(e_gt), self.data["f"].append(f_gt)
img_path1, img_path2 = os.path.join(
"yfcc100m", seq, "test", name_list[index1]
), os.path.join("yfcc100m", seq, "test", name_list[index2])
dump_seq_dir = os.path.join(
self.config["feature_dump_dir"], seq, "test"
)
fea_path1, fea_path2 = os.path.join(
dump_seq_dir,
name_list[index1].split("/")[-1]
+ "_"
+ self.config["extractor"]["name"]
+ "_"
+ str(self.config["extractor"]["num_kpt"])
+ ".hdf5",
), os.path.join(
dump_seq_dir,
name_list[index2].split("/")[-1]
+ "_"
+ self.config["extractor"]["name"]
+ "_"
+ str(self.config["extractor"]["num_kpt"])
+ ".hdf5",
)
self.data["img_path1"].append(img_path1), self.data["img_path2"].append(
img_path2
)
self.data["fea_path1"].append(fea_path1), self.data["fea_path2"].append(
fea_path2
)
self.form_standard_dataset()
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