Github/Stable-Diffusion-for-Remote-Sensing-Image-Generation
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xiaoyuan1996 2023-05-06 22:21:59 +08:00
parent f514f06b1e
commit 886c883561
4 changed files with 12 additions and 3 deletions
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3
configs/stable-diffusion/RSITMD.yaml
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@ -79,6 +79,9 @@ data:
target: ldm.data.simple.hf_dataset_RSITMD target: ldm.data.simple.hf_dataset_RSITMD
params: params:
name: RSITMD-captions name: RSITMD-captions
data_path: ./data/RSITMD
train_json_path: ./data/RSITMD/hf_train.json
val_json_path: ./data/RSITMD/hf_val.json
image_transforms: image_transforms:
- target: torchvision.transforms.Resize - target: torchvision.transforms.Resize
params: params:

1
data/RSITMD/hf_train.json Normal file
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data/RSITMD/hf_val.json Normal file
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10
ldm/data/simple.py
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@ -1,3 +1,4 @@
import os
from typing import Dict from typing import Dict
import numpy as np import numpy as np
from omegaconf import DictConfig, ListConfig from omegaconf import DictConfig, ListConfig
@ -298,6 +299,9 @@ def hf_dataset(
def hf_dataset_RSITMD( def hf_dataset_RSITMD(
name, name,
data_path,
train_json_path,
val_json_path,
image_transforms=[], image_transforms=[],
image_column="image", image_column="image",
text_column="text", text_column="text",
@ -309,8 +313,8 @@ def hf_dataset_RSITMD(
""" """
data_files = { data_files = {
"train": "/mmu_nlp_ssd/yuanzhiqiang/dif/data/RSITMD/hf_train.json", "train": train_json_path,
"validation": "/mmu_nlp_ssd/yuanzhiqiang/dif/data/RSITMD/hf_val.json" "validation": val_json_path
} }
ds = load_dataset("json", data_files=data_files, field="data") ds = load_dataset("json", data_files=data_files, field="data")
@ -326,7 +330,7 @@ def hf_dataset_RSITMD(
assert text_column in ds.column_names, f"Didn't find column {text_column} in {ds.column_names}" assert text_column in ds.column_names, f"Didn't find column {text_column} in {ds.column_names}"
def pre_process(examples): def pre_process(examples):
examples['image'] = [Image.open(x) for x in examples['image']] examples['image'] = [Image.open(os.path.join(data_path, x)) for x in examples['image']]
processed = {} processed = {}
processed[image_key] = [tform(im) for im in examples[image_column]] processed[image_key] = [tform(im) for im in examples[image_column]]