Comments (3)
Hmmm, there might be something going wrong with the images that you pass to the model. Did the code for you work with the English version?
from concept.
Hmmm, there might be something going wrong with the images that you pass to the model. Did the code for you work with the English version?
Yes, the English model "clip-ViT-B-32" is working fine, while "clip-ViT-B-32-multilingual-v1" throws the error.
I've tried changing the dataset (all images in .jpeg format), and the same problem happens.
from concept.
Unfortunately, then there seems to be an issue with that specific model processing the images. You could try to embed the images using SentenceTransformers directly and then pass the embeddings to to fit_transform
using the parameter image_embeddings
. That way, you can also check if there is an issue with a specific image in your dataset.
from concept.
Related Issues (19)
- Index Error: index out of bounds error for visualize concepts HOT 7
- OSError: [Errno 24] Too many open files: 'photos/icnZ2R8PcDs.jpg' HOT 3
- ValueError: operands could not be broadcast together with shapes (4,224,224) (3,) HOT 9
- Exemplar dict is not serializable HOT 3
- Pandas key error during model fitting HOT 9
- TypeError: __init__() got an unexpected keyword argument 'cachedir' HOT 1
- How can we get probabilities for all clusters in transform function? HOT 3
- Saving the model HOT 2
- AttributeError: 'CountVectorizer' object has no attribute 'get_feature_names' HOT 5
- discussion on different concepts results HOT 2
- sentence-transformers version HOT 2
- AttributeError: 'ConceptModel' object has no attribute 'image_cluster_df' HOT 3
- TypeError: Cannot use scipy.linalg.eigh for sparse A with k >= N. Use scipy.linalg.eigh(A.toarray()) or reduce k. HOT 1
- TypeError: Cannot use scipy.linalg.eigh for sparse A with k >= N. Use scipy.linalg.eigh(A.toarray()) or reduce k. HOT 1
- Questions HOT 4
- Question about the Function transform HOT 7
- Saving the model HOT 2
- Using GPU while processing concepts HOT 2
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from concept.