diff --git a/ppcls/configs/Cartoonface/ResNet50_icartoon.yaml b/ppcls/configs/Cartoonface/ResNet50_icartoon.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f18f3346bd6abf6a997ee1461cc815799c61d6a6 --- /dev/null +++ b/ppcls/configs/Cartoonface/ResNet50_icartoon.yaml @@ -0,0 +1,141 @@ +# global configs +Global: + checkpoints: null + pretrained_model: null + output_dir: "./output/" + device: "gpu" + class_num: 5013 + save_interval: 1 + eval_mode: "retrieval" + eval_during_train: True + eval_interval: 1 + epochs: 120 + print_batch_step: 10 + use_visualdl: False + image_shape: [3, 224, 224] + infer_imgs: + save_inference_dir: "./output" + feature_normalize: True + +Arch: + name: "RecModel" + Backbone: + name: "ResNet50" + pretrained: True + BackboneStopLayer: + name: "flatten_0" + output_dim: 2048 + Head: + name: "FC" + class_num: 5013 + embedding_size: 2048 + # margin: 0.5 + # scale: 80 + infer_output_key: "features" + infer_add_softmax: "false" + +Loss: + Train: + - CELoss: + weight: 1.0 + # - TripletLoss: + # margin: 0.1 + # weight: 0.1 + Eval: + - CELoss: + weight: 1.0 + +Optimizer: + name: Momentum + momentum: 0.9 + lr: + name: Piecewise + learning_rate: 0.1 + decay_epochs: [30, 60, 90] + values: [0.1, 0.01, 0.001, 0.0001] + regularizer: + name: 'L2' + coeff: 0.0001 + +DataLoader: + Train: + dataset: + name: ICartoonDataset + image_root: "./dataset/iCartoonFace" + cls_label_path: "./dataset/iCartoonFace/train_list.txt" + transform_ops: + - RandCropImage: + size: 224 + - RandFlipImage: + flip_code: 1 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + sampler: + name: DistributedBatchSampler + #num_instances: 2 + batch_size: 256 + drop_last: False + shuffle: True + loader: + num_workers: 6 + use_shared_memory: False + + Eval: + Query: + dataset: + name: ICartoonDataset + image_root: "./dataset/iCartoonFace" + cls_label_path: "./dataset/iCartoonFace/query.txt" + transform_ops: + - ResizeImage: + resize_short: 256 + - CropImage: + size: 224 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + sampler: + name: DistributedBatchSampler + batch_size: 64 + drop_last: False + shuffle: False + loader: + num_workers: 6 + use_shared_memory: False + + Gallery: + dataset: + name: ICartoonDataset + image_root: "./dataset/iCartoonFace" + cls_label_path: "./dataset/iCartoonFace/gallery.txt" + transform_ops: + - ResizeImage: + resize_short: 256 + - CropImage: + size: 224 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + sampler: + name: DistributedBatchSampler + batch_size: 64 + drop_last: False + shuffle: False + loader: + num_workers: 6 + use_shared_memory: False + +Metric: + Train: + - TopkAcc: + topk: [1, 5] + Eval: + - Recallk: + topk: 1 diff --git a/ppcls/data/__init__.py b/ppcls/data/__init__.py index fca8bf093259e4f42e4c5af5a3de125a2f81cf61..5f64e9031bc1421e4ae68849e1da14e831c847e9 100644 --- a/ppcls/data/__init__.py +++ b/ppcls/data/__init__.py @@ -25,6 +25,7 @@ from ppcls.data.dataloader.imagenet_dataset import ImageNetDataset from ppcls.data.dataloader.multilabel_dataset import MultiLabelDataset from ppcls.data.dataloader.common_dataset import create_operators from ppcls.data.dataloader.vehicle_dataset import CompCars, VeriWild +from ppcls.data.dataloader.icartoon_dataset import ICartoonDataset # sampler from ppcls.data.dataloader.DistributedRandomIdentitySampler import DistributedRandomIdentitySampler diff --git a/ppcls/data/dataloader/icartoon_dataset.py b/ppcls/data/dataloader/icartoon_dataset.py new file mode 100644 index 0000000000000000000000000000000000000000..32f6038f92667aee0c773ede58bd101218185b96 --- /dev/null +++ b/ppcls/data/dataloader/icartoon_dataset.py @@ -0,0 +1,40 @@ +# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import print_function + +import numpy as np +import os + +from .common_dataset import CommonDataset + + +class ICartoonDataset(CommonDataset): + def _load_anno(self, seed=None): + assert os.path.exists(self._cls_path) + assert os.path.exists(self._img_root) + self.images = [] + self.labels = [] + + with open(self._cls_path) as fd: + lines = fd.readlines() + if seed is not None: + np.random.RandomState(seed).shuffle(lines) + else: + np.random.shuffle(lines) + for l in lines: + l = l.strip().split("\t") + self.images.append(os.path.join(self._img_root, l[0][2:])) + self.labels.append(int(l[1])) + assert os.path.exists(self.images[-1])