Spaces:
Sleeping
Sleeping
# Expects Visual Genome to be downloaded to `data/vg` and the TallyQA test set | |
# to be present at `data/tallyqa/test.json`. | |
# | |
# Steps to download Visual Genome and TallyQA: | |
# | |
# mkdir -p data/vg/VG_100K | |
# mkdir -p data/vg/VG_100K_2 | |
# mkdir -p data/tallyqa | |
# wget -P data/vg/VG_100K_2/ https://cs.stanford.edu/people/rak248/VG_100K_2/images2.zip | |
# wget -P data/vg/VG_100K/ https://cs.stanford.edu/people/rak248/VG_100K_2/images.zip | |
# wget -P data/tallyqa/ https://github.com/manoja328/TallyQA_dataset/raw/master/tallyqa.zip | |
# unzip data/vg/VG_100K_2/images2.zip -d data/vg/ | |
# unzip data/vg/VG_100K/images.zip -d data/vg/ | |
# unzip data/tallyqa/tallyqa.zip -d data/tallyqa/ | |
# rm data/vg/VG_100K_2/images2.zip | |
# rm data/vg/VG_100K/images.zip | |
# rm data/tallyqa/tallyqa.zip | |
import json | |
from PIL import Image | |
from tqdm import tqdm | |
from transformers import AutoTokenizer | |
from ..hf import Moondream, detect_device | |
BATCH_SIZE = 16 | |
DEVICE, DTYPE = detect_device() | |
model_id = "vikhyatk/moondream2" | |
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True) | |
model = Moondream.from_pretrained( | |
model_id, | |
attn_implementation="flash_attention_2", | |
torch_dtype=DTYPE, | |
device_map={"": DEVICE}, | |
) | |
model.eval() | |
total = 0 | |
total_simple = 0 | |
correct = 0 | |
correct_simple = 0 | |
# Iterate over tallyqa_test in batches of BATCH_SIZE | |
tallyqa_test = json.load(open("data/tallyqa/test.json")) | |
for i in tqdm(range(0, len(tallyqa_test), BATCH_SIZE)): | |
batch = tallyqa_test[i : i + BATCH_SIZE] | |
images = [Image.open(f"data/vg/{item['image']}") for item in batch] | |
questions = [ | |
item["question"] + " Answer in a word or phrase only." for item in batch | |
] | |
answers = model.batch_answer( | |
images=images, prompts=questions, tokenizer=tokenizer, max_new_tokens=10 | |
) | |
for answer, item in zip(answers, batch): | |
is_simple = item["issimple"] | |
is_correct = 1 if str(item["answer"]) == answer else 0 | |
total += 1 | |
correct += is_correct | |
if is_simple: | |
total_simple += 1 | |
correct_simple += is_correct | |
print( | |
f"Simple: {total_simple}, Correct: {correct_simple}, Accuracy: {correct_simple*100.0/total_simple}" | |
) | |
print(f"Total: {total}, Correct: {correct}, Accuracy: {correct*100.0/total}") | |