Datasets:

Modalities:
Image
Languages:
English
Dataset Viewer
The dataset viewer is not available for this dataset.
The JWT signature verification failed. Check the signing key and the algorithm.
Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Dataset Summary

image/png

DeepShade is a multimodal dataset designed for shade simulation via text-conditioned image generation. It captures realistic outdoor scenes and their corresponding shade conditions over time, enabling supervised training of diffusion-based models that can simulate sun-shade transitions based on spatial layout and temporal context.

The dataset was introduced in the DeepShade project (IJCAI 2025 submission), and it supports research in text-to-image generation.

Dataset Files Structure:

Each city has a dedicated zip folder which contains source, target and the test and train json files There is one common zip file for all the satellite images of all the cities

Dataset Structure

Data Modality: Multimodal (Image, Text, Time) Number of samples: ~100,000 Resolution: 1024×1024 images

Formats: .png images (rendered) .json metadata files with the following fields:

  1. Source image file path
  2. Target image file path
  3. Prompt
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