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Add PIL fallback for image resizing #232

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Add PIL fallback for image resizing #232

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849652a
Add PIL fallback for image resizing when PyVips is not available
openhands-agent Jan 26, 2025
bd7af47
Add PIL fallback for image resizing when PyVips is not available
openhands-agent Jan 26, 2025
71c46c3
Move PIL import to top level
openhands-agent Jan 26, 2025
08119fe
Move PIL import inside except block
openhands-agent Jan 28, 2025
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47 changes: 33 additions & 14 deletions moondream/torch/image_crops.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,15 @@
import math
import numpy as np
import torch
import pyvips

from typing import TypedDict

try:
import pyvips
HAVE_PYVIPS = True
except ImportError:
from PIL import Image
HAVE_PYVIPS = False


def select_tiling(
height: int, width: int, crop_size: int, max_crops: int
Expand Down Expand Up @@ -113,18 +118,32 @@ def overlap_crop_image(
tiling[1] * crop_window_size + total_margin_pixels,
)

# Convert to vips for resizing
vips_image = pyvips.Image.new_from_array(image)
scale_x = target_size[1] / image.shape[1]
scale_y = target_size[0] / image.shape[0]
resized = vips_image.resize(scale_x, vscale=scale_y)
image = resized.numpy()

# Create global crop
scale_x = base_size[1] / vips_image.width
scale_y = base_size[0] / vips_image.height
global_vips = vips_image.resize(scale_x, vscale=scale_y)
crops[0] = global_vips.numpy()
if HAVE_PYVIPS:
# Convert to vips for resizing
vips_image = pyvips.Image.new_from_array(image)
scale_x = target_size[1] / image.shape[1]
scale_y = target_size[0] / image.shape[0]
resized = vips_image.resize(scale_x, vscale=scale_y)
image = resized.numpy()

# Create global crop
scale_x = base_size[1] / vips_image.width
scale_y = base_size[0] / vips_image.height
global_vips = vips_image.resize(scale_x, vscale=scale_y)
crops[0] = global_vips.numpy()
else:
# Use PIL for resizing
pil_image = Image.fromarray(image)
resized = pil_image.resize(
(target_size[1], target_size[0]), Image.Resampling.LANCZOS
)
image = np.array(resized)

# Create global crop
global_pil = pil_image.resize(
(base_size[1], base_size[0]), Image.Resampling.LANCZOS
)
crops[0] = np.array(global_pil)

for i in range(tiling[0]):
for j in range(tiling[1]):
Expand Down