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Refactor batch processing in calculate_coco_features.py #741

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Refactor batch processing in calculate_coco_features.py #741

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34 changes: 19 additions & 15 deletions app/calculate_coco_features.py
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Original file line number Diff line number Diff line change
@@ -1,9 +1,7 @@
"""
# Copyright (c) 2022, salesforce.com, inc.
# All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
# For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
"""
# Copyright (c) 2022, salesforce.com, inc.
# All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
# For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause

from PIL import Image
import requests
Expand All @@ -18,7 +16,6 @@

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")


def load_demo_image():
img_url = (
"https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg"
Expand All @@ -34,6 +31,17 @@ def read_img(filepath):
return raw_image


def process_batch(images_in_batch, filepaths_in_batch, feature_extractor, caption, path2feat):
images_in_batch = torch.cat(images_in_batch, dim=0).to(device)
with torch.no_grad():
image_features = feature_extractor(
images_in_batch, caption, mode="image", normalized=True
)[:, 0]

for filepath, image_feat in zip(filepaths_in_batch, image_features):
path2feat[os.path.basename(filepath)] = image_feat.detach().cpu()
return path2feat

# model
model_url = "https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base.pth"
feature_extractor = BlipFeatureExtractor(pretrained=model_url)
Expand Down Expand Up @@ -62,14 +70,7 @@ def read_img(filepath):

for i, filename in enumerate(filepaths):
if i % bsz == 0 and i > 0:
images_in_batch = torch.cat(images_in_batch, dim=0).to(device)
with torch.no_grad():
image_features = feature_extractor(
images_in_batch, caption, mode="image", normalized=True
)[:, 0]

for filepath, image_feat in zip(filepaths_in_batch, image_features):
path2feat[os.path.basename(filepath)] = image_feat.detach().cpu()
path2feat = process_batch(images_in_batch, filepaths_in_batch, feature_extractor, caption, path2feat)

images_in_batch = []
filepaths_in_batch = []
Expand All @@ -84,4 +85,7 @@ def read_img(filepath):
images_in_batch.append(image)
filepaths_in_batch.append(filepath)

path2feat = process_batch(images_in_batch, filepaths_in_batch, feature_extractor, caption, path2feat) # process remaining images

torch.save(path2feat, "path2feat_coco_train2014.pth")