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yadonglu
2024-12-09 12:26:04 -08:00
parent 075f349ea1
commit 669efd3611
6 changed files with 1149 additions and 30 deletions
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42
gradio_demo.py
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@@ -11,10 +11,7 @@ import base64, os
from utils import check_ocr_box, get_yolo_model, get_caption_model_processor, get_som_labeled_img
import torch
from PIL import Image
yolo_model = get_yolo_model(model_path='weights/icon_detect/best.pt')
caption_model_processor = get_caption_model_processor(model_name="florence2", model_name_or_path="weights/icon_caption_florence")
# caption_model_processor = get_caption_model_processor(model_name="blip2", model_name_or_path="weights/icon_caption_blip2")
import argparse
@@ -39,9 +36,9 @@ def process(
box_threshold,
iou_threshold,
use_paddleocr,
imgsz
imgsz,
icon_process_batch_size,
) -> Optional[Image.Image]:
image_save_path = 'imgs/saved_image_demo.png'
image_input.save(image_save_path)
image = Image.open(image_save_path)
@@ -57,13 +54,26 @@ def process(
ocr_bbox_rslt, is_goal_filtered = check_ocr_box(image_save_path, display_img = False, output_bb_format='xyxy', goal_filtering=None, easyocr_args={'paragraph': False, 'text_threshold':0.9}, use_paddleocr=use_paddleocr)
text, ocr_bbox = ocr_bbox_rslt
# print('prompt:', prompt)
dino_labled_img, label_coordinates, parsed_content_list = get_som_labeled_img(image_save_path, yolo_model, BOX_TRESHOLD = box_threshold, output_coord_in_ratio=True, ocr_bbox=ocr_bbox,draw_bbox_config=draw_bbox_config, caption_model_processor=caption_model_processor, ocr_text=text,iou_threshold=iou_threshold, imgsz=imgsz)
dino_labled_img, label_coordinates, parsed_content_list = get_som_labeled_img(image_save_path, yolo_model, BOX_TRESHOLD = box_threshold, output_coord_in_ratio=True, ocr_bbox=ocr_bbox,draw_bbox_config=draw_bbox_config, caption_model_processor=caption_model_processor, ocr_text=text,iou_threshold=iou_threshold, imgsz=imgsz, batch_size=icon_process_batch_size)
image = Image.open(io.BytesIO(base64.b64decode(dino_labled_img)))
print('finish processing')
parsed_content_list = '\n'.join(parsed_content_list)
# parsed_content_list = '\n'.join(parsed_content_list)
parsed_content_list = '\n'.join([f'type: {x['type']}, content: {x["content"]}, interactivity: {x["interactivity"]}' for x in parsed_content_list])
return image, str(parsed_content_list)
parser = argparse.ArgumentParser(description='Process model paths and names.')
parser.add_argument('--icon_detect_model', type=str, required=True, default='weights/icon_detect/best.pt', help='Path to the YOLO model weights')
parser.add_argument('--icon_caption_model', type=str, required=True, default='florence2', help='Name of the caption model')
args = parser.parse_args()
icon_detect_model, icon_caption_model = args.icon_detect_model, args.icon_caption_model
yolo_model = get_yolo_model(model_path=icon_detect_model)
if icon_caption_model == 'florence2':
caption_model_processor = get_caption_model_processor(model_name="florence2", model_name_or_path="weights/icon_caption_florence")
elif icon_caption_model == 'blip2':
caption_model_processor = get_caption_model_processor(model_name="blip2", model_name_or_path="weights/icon_caption_blip2")
with gr.Blocks() as demo:
gr.Markdown(MARKDOWN)
@@ -78,9 +88,11 @@ with gr.Blocks() as demo:
iou_threshold_component = gr.Slider(
label='IOU Threshold', minimum=0.01, maximum=1.0, step=0.01, value=0.1)
use_paddleocr_component = gr.Checkbox(
label='Use PaddleOCR', value=True)
label='Use PaddleOCR', value=False)
imgsz_component = gr.Slider(
label='Icon Detect Image Size', minimum=640, maximum=1920, step=32, value=640)
label='Icon Detect Image Size', minimum=640, maximum=3200, step=32, value=1920)
icon_process_batch_size_component = gr.Slider(
label='Icon Process Batch Size', minimum=1, maximum=256, step=1, value=64)
submit_button_component = gr.Button(
value='Submit', variant='primary')
with gr.Column():
@@ -94,10 +106,16 @@ with gr.Blocks() as demo:
box_threshold_component,
iou_threshold_component,
use_paddleocr_component,
imgsz_component
imgsz_component,
icon_process_batch_size_component
],
outputs=[image_output_component, text_output_component]
)
# demo.launch(debug=False, show_error=True, share=True)
demo.launch(share=True, server_port=7861, server_name='0.0.0.0')
demo.launch(share=True, server_port=7861, server_name='0.0.0.0')
# python gradio_demo.py --icon_detect_model weights/icon_detect/best.pt --icon_caption_model florence2
# python gradio_demo.py --icon_detect_model weights/icon_detect_v1_5/model_v1_5.pt --icon_caption_model florence2