mirror of
https://github.com/NVIDIA/Model-Optimizer.git
synced 2026-10-22 06:21:37 +08:00
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2023-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# 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.
|
|
|
|
import json
|
|
from collections import defaultdict
|
|
from pathlib import Path
|
|
|
|
import numpy as np
|
|
import torch
|
|
from PIL import Image
|
|
|
|
|
|
def load_json_file(file_path: Path):
|
|
with open(file_path) as f:
|
|
data = json.load(f)
|
|
return data
|
|
|
|
|
|
def convert_img2tensor(image_path):
|
|
image_data = Image.open(image_path).convert("RGB")
|
|
image_tensor = torch.from_numpy(np.array(image_data)).permute(2, 0, 1)
|
|
return image_tensor
|
|
|
|
|
|
def reorganize_data(data):
|
|
"""
|
|
data: a list of dicts, each dict like:
|
|
{
|
|
"prompt": <string>,
|
|
"images": {
|
|
"modelA": <path1>,
|
|
"modelB": <path2>,
|
|
...
|
|
}
|
|
}
|
|
returns: dict of model_name -> list of { "prompt": <>, "image": <> }
|
|
"""
|
|
model_dict = defaultdict(list)
|
|
|
|
for item in data:
|
|
prompt = item["prompt"]
|
|
for model_name, image_path in item["images"].items():
|
|
model_dict[model_name].append({"prompt": prompt, "image": image_path})
|
|
|
|
return dict(model_dict)
|