Hi, It is definitely a great tool!
but when i run the demo script:
"from PIL import Image
from clip_interrogator import Config, Interrogator
image = Image.open(image_path).convert('RGB')
ci = Interrogator(Config(clip_model_name="ViT-L-14/openai"))
print(ci.interrogate(image))"
the error appears:
Loaded CLIP model and data in 11.34 seconds.
/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/generation/utils.py:2256: UserWarning: MPS: no support for int64 min/max ops, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/ReduceOps.mm:1271.)
if unfinished_sequences.max() == 0 or stopping_criteria(input_ids, scores):
Traceback (most recent call last):
File "/Users/leon/machinelearning/clipdemo/main.py", line 20, in
imageAnnotation('images/dog389.jpg')
File "/Users/leon/machinelearning/clipdemo/main.py", line 15, in imageAnnotation
print(ci.interrogate(image))
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/clip_interrogator/clip_interrogator.py", line 244, in interrogate
caption = caption or self.generate_caption(image)
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/clip_interrogator/clip_interrogator.py", line 195, in generate_caption
return self.caption_processor.batch_decode(tokens, skip_special_tokens=True)[0].strip()
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/models/blip/processing_blip.py", line 135, in batch_decode
return self.tokenizer.batch_decode(*args, **kwargs)
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3437, in batch_decode
return [
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3438, in
self.decode(
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3476, in decode
return self._decode(
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_fast.py", line 549, in _decode
text = self._tokenizer.decode(token_ids, skip_special_tokens=skip_special_tokens)
OverflowError: out of range integral type conversion attempted
environment is python 3.9. Mac OS 13.2.1 (22D68). with PyCharm 2022.3.3 (Community Edition)
It is very appreciate if anyone can help. thx a lot!
Hi, It is definitely a great tool! but when i run the demo script: "from PIL import Image from clip_interrogator import Config, Interrogator image = Image.open(image_path).convert('RGB') ci = Interrogator(Config(clip_model_name="ViT-L-14/openai")) print(ci.interrogate(image))"
the error appears: Loaded CLIP model and data in 11.34 seconds. /Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/generation/utils.py:2256: UserWarning: MPS: no support for int64 min/max ops, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/ReduceOps.mm:1271.) if unfinished_sequences.max() == 0 or stopping_criteria(input_ids, scores): Traceback (most recent call last): File "/Users/leon/machinelearning/clipdemo/main.py", line 20, in
imageAnnotation('images/dog389.jpg')
File "/Users/leon/machinelearning/clipdemo/main.py", line 15, in imageAnnotation
print(ci.interrogate(image))
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/clip_interrogator/clip_interrogator.py", line 244, in interrogate
caption = caption or self.generate_caption(image)
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/clip_interrogator/clip_interrogator.py", line 195, in generate_caption
return self.caption_processor.batch_decode(tokens, skip_special_tokens=True)[0].strip()
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/models/blip/processing_blip.py", line 135, in batch_decode
return self.tokenizer.batch_decode(*args, **kwargs)
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3437, in batch_decode
return [
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3438, in
self.decode(
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 3476, in decode
return self._decode(
File "/Users/leon/machinelearning/clipdemo/venv/lib/python3.9/site-packages/transformers/tokenization_utils_fast.py", line 549, in _decode
text = self._tokenizer.decode(token_ids, skip_special_tokens=skip_special_tokens)
OverflowError: out of range integral type conversion attempted
environment is python 3.9. Mac OS 13.2.1 (22D68). with PyCharm 2022.3.3 (Community Edition)
It is very appreciate if anyone can help. thx a lot!