TDSFT_2 / LLaVA-Next-3D /data_precessing /box_visualization.py
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from PIL import Image, ImageDraw, ImageFont
import json
import os
from diffusers.utils import make_image_grid
import pdb
def draw_bbox_on_image(path, bbox_normalized):
# 打开图像文件
img = Image.open(path)
width, height = img.size
x1 = int(bbox_normalized[0] * width)
y1 = int(bbox_normalized[1] * height)
x2 = int(bbox_normalized[2] * width)
y2 = int(bbox_normalized[3] * height)
draw = ImageDraw.Draw(img)
draw.rectangle([(x1, y1), (x2, y2)], outline='red', width=2)
return img
result_file = 'results/scanrefer/prompt-llavanext-qwen-uniform-16bs-scanrefer-wosam-uniform.jsonl'
visual_num = 1000
with open(result_file, 'r') as f:
i = 0
for line in f:
i += 1
if i >= visual_num:
break
item = json.loads(line)
output_dir = result_file.replace('.jsonl', '')
os.makedirs(output_dir, exist_ok=True)
pred_response = item['pred_response']
description = item['prompt'].split('\n')[-1]
sample_id = str(item['sample_id'])
sample_dir = os.path.join(output_dir, sample_id)
image_list = []
for path, box in pred_response.items():
try:
drawn_image = draw_bbox_on_image(path, box)
image_list.append(drawn_image)
# drawn_image.save(os.path.join(sample_dir, path.split('/')[-1]))
except:
continue
image_num = min(5, len(image_list))
image_list = image_list[:image_num]
concat_image = make_image_grid(image_list, 1, image_num)
draw = ImageDraw.Draw(concat_image)
font = ImageFont.load_default(size=80)
draw.text((10, 10), description, fill='green', font=font)
concat_image.save(os.path.join(sample_dir+'.jpg'))