@clin1223
Hi, thanks for your significant work!
We want to reproduce the COCO zero-shot results In Table 3.
We generate the text embeddings via clip-vit-large-patch14-336. We replace the ZERO_SHOT_WEIGHT with the generated embeds.
Unfortunately, the results are 0.
Could you please give some points to us? Could you please provide the corresponding COCO-80-embeddings?
Thanks! Have a nice day!
By the way, we generate the COCO-80-embeddings as follows.
model_path = "clip-vit-large-patch14-336"
model = CLIPTextModel.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)
inputs = tokenizer(['a '+ class], padding=True, return_tensors="pt")
outputs = model(**inputs)
text_features = outputs.pooler_output
We obtain a numpy array, 80* 768.
@clin1223
Hi, thanks for your significant work!
We want to reproduce the COCO zero-shot results In Table 3.
We generate the text embeddings via clip-vit-large-patch14-336. We replace the ZERO_SHOT_WEIGHT with the generated embeds.
Unfortunately, the results are 0.
Could you please give some points to us? Could you please provide the corresponding COCO-80-embeddings?
Thanks! Have a nice day!
By the way, we generate the COCO-80-embeddings as follows.
We obtain a numpy array, 80* 768.