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Fix: avoid double-rescaling of images in the BLIP-2 inference pipeline #11

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Fix: avoid double-rescaling of images in the BLIP-2 inference pipeline #11

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4 changes: 2 additions & 2 deletions hydra_vl4ai/tool/blip.py
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Original file line number Diff line number Diff line change
Expand Up @@ -52,7 +52,7 @@ def __init__(self, gpu_number=0, blip_v2_model_type="blip2-flan-t5-xxl"):

@torch.no_grad()
def caption(self, image, prompt=None):
inputs = self.processor(images=image, text=prompt, return_tensors="pt").to(self.dev)
inputs = self.processor(images=image, text=prompt, return_tensors="pt", do_rescale=False).to(self.dev)
generated_ids = self.model.generate(**inputs, length_penalty=1., num_beams=5, max_length=30, min_length=1,
do_sample=False, top_p=0.9, repetition_penalty=1.0,
num_return_sequences=1, temperature=1)
Expand All @@ -78,7 +78,7 @@ def pre_question(self, question):

@torch.no_grad()
def qa(self, image, question):
inputs = self.processor(images=image, text=question, return_tensors="pt", padding="longest").to(self.dev)
inputs = self.processor(images=image, text=question, return_tensors="pt", padding="longest", do_rescale=False).to(self.dev)
generated_ids = self.model.generate(**inputs, length_penalty=-1, num_beams=5, max_length=10, min_length=1,
do_sample=False, top_p=0.9, repetition_penalty=1.0,
num_return_sequences=1, temperature=1)
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