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Running
on
T4
Running
on
T4
File size: 1,395 Bytes
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import os
cap_base = 'samples/caption'
cap = [
dict(cap_objaid=os.path.splitext(x)[0], dispi=os.path.join(cap_base, x))
for x in sorted(os.listdir(cap_base))
]
cls_base = 'samples/classification'
classification = [
dict(cls_objaid=os.path.splitext(x)[0], dispi=os.path.join(cls_base, x))
for x in sorted(os.listdir(cls_base))
]
sd_base = 'samples/sd'
sd_texts = {
'b8db8dc5caad4fa5842a9ed6dbd2e9d6': 'falcon',
'ff2875fb1a5b4771805a5fd35c8fe7bb': 'in the woods',
'tpvzmLUXAURQ7ZxccJIBZvcIDlr': 'above the fields'
}
sd = [
dict(
sd_objaid=os.path.splitext(x)[0],
dispi=os.path.join(sd_base, x),
sdtprompt=sd_texts.get(os.path.splitext(x)[0], '')
)
for x in sorted(os.listdir(sd_base))
]
retrieval_texts = """
shark
swordfish
dolphin
goldfish
high heels
boots
slippers
sneakers
tiki mug
viking mug
animal-shaped mug
travel mug
white conical mug
green cubic mug
blue spherical mug
orange cylinder mug
""".splitlines()
retrieval_texts = [x.strip() for x in retrieval_texts if x.strip()]
pret_base = 'samples/retrieval-pc'
pret = [
dict(retpc_objaid=os.path.splitext(x)[0], dispi=os.path.join(pret_base, x))
for x in sorted(os.listdir(pret_base))
]
iret_base = 'samples/retrieval-img'
iret = [
dict(rimageinput=os.path.join(iret_base, x), dispi=os.path.join(iret_base, x))
for x in sorted(os.listdir(iret_base))
]
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