Files
JoyD/TARS/UI-TARS/codes/tests/inference_test.py
2025-10-31 11:12:44 +08:00

100 lines
3.1 KiB
Python

import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from PIL import Image
import matplotlib.pyplot as plt
import json
import base64
from io import BytesIO
from PIL import Image
import math
from ui_tars.action_parser import IMAGE_FACTOR, MIN_PIXELS, MAX_PIXELS, MAX_RATIO
def round_by_factor(number: int, factor: int) -> int:
"""Returns the closest integer to 'number' that is divisible by 'factor'."""
return round(number / factor) * factor
def ceil_by_factor(number: int, factor: int) -> int:
"""Returns the smallest integer greater than or equal to 'number' that is divisible by 'factor'."""
return math.ceil(number / factor) * factor
def floor_by_factor(number: int, factor: int) -> int:
"""Returns the largest integer less than or equal to 'number' that is divisible by 'factor'."""
return math.floor(number / factor) * factor
def smart_resize(
height: int,
width: int,
factor: int = IMAGE_FACTOR,
min_pixels: int = MIN_PIXELS,
max_pixels: int = MAX_PIXELS,
) -> tuple[int, int]:
"""
Rescales the image so that the following conditions are met:
1. Both dimensions (height and width) are divisible by 'factor'.
2. The total number of pixels is within the range ['min_pixels', 'max_pixels'].
3. The aspect ratio of the image is maintained as closely as possible.
"""
if max(height, width) / min(height, width) > MAX_RATIO:
raise ValueError(
f"absolute aspect ratio must be smaller than {MAX_RATIO}, got {max(height, width) / min(height, width)}"
)
h_bar = max(factor, round_by_factor(height, factor))
w_bar = max(factor, round_by_factor(width, factor))
if h_bar * w_bar > max_pixels:
beta = math.sqrt((height * width) / max_pixels)
h_bar = floor_by_factor(height / beta, factor)
w_bar = floor_by_factor(width / beta, factor)
elif h_bar * w_bar < min_pixels:
beta = math.sqrt(min_pixels / (height * width))
h_bar = ceil_by_factor(height * beta, factor)
w_bar = ceil_by_factor(width * beta, factor)
return h_bar, w_bar
if __name__ == '__main__':
# Assume model output
model_raw_response = """Thought: xxx
Action: click(start_box='(197,525)')"""
# Please use re to parse the coordinate values
model_output_width = 197
model_output_height = 525
# Open the image
img = Image.open('./data/coordinate_process_image.png')
width, height = img.size
print(f'Original coordinate: {width}, {height}')
# Calculate the new dimensions
new_height, new_width = smart_resize(height, width)
new_coordinate = (
int(model_output_width / new_width * width),
int(model_output_height / new_height * height),
)
print(f'Resized dimensions: {new_width}, {new_height}')
print(new_coordinate)
# Display the image
plt.imshow(img)
plt.scatter(
[new_coordinate[0]], [new_coordinate[1]], c='red', s=50
) # Mark the point with a red dot
plt.title('Visualize Coordinate')
plt.axis('off') # Set to 'off' to hide the axes
plt.savefig('./data/coordinate_process_image_som.png', dpi=350)