Compare commits
1 Commits
main
...
fix/11_sim
Author | SHA1 | Date |
---|---|---|
SkalskiP | 0c2931b8cd | 2 years ago |
9 changed files with 29 additions and 1701 deletions
@ -1,125 +0,0 @@ |
||||
import argparse |
||||
from functools import partial |
||||
import cv2 |
||||
import requests |
||||
import os |
||||
from io import BytesIO |
||||
from PIL import Image |
||||
import numpy as np |
||||
from pathlib import Path |
||||
|
||||
|
||||
import warnings |
||||
|
||||
import torch |
||||
|
||||
# prepare the environment |
||||
os.system("python setup.py build develop --user") |
||||
os.system("pip install packaging==21.3") |
||||
os.system("pip install gradio") |
||||
|
||||
|
||||
warnings.filterwarnings("ignore") |
||||
|
||||
import gradio as gr |
||||
|
||||
from groundingdino.models import build_model |
||||
from groundingdino.util.slconfig import SLConfig |
||||
from groundingdino.util.utils import clean_state_dict |
||||
from groundingdino.util.inference import annotate, load_image, predict |
||||
import groundingdino.datasets.transforms as T |
||||
|
||||
from huggingface_hub import hf_hub_download |
||||
|
||||
|
||||
|
||||
# Use this command for evaluate the Grounding DINO model |
||||
config_file = "groundingdino/config/GroundingDINO_SwinT_OGC.py" |
||||
ckpt_repo_id = "ShilongLiu/GroundingDINO" |
||||
ckpt_filenmae = "groundingdino_swint_ogc.pth" |
||||
|
||||
|
||||
def load_model_hf(model_config_path, repo_id, filename, device='cpu'): |
||||
args = SLConfig.fromfile(model_config_path) |
||||
model = build_model(args) |
||||
args.device = device |
||||
|
||||
cache_file = hf_hub_download(repo_id=repo_id, filename=filename) |
||||
checkpoint = torch.load(cache_file, map_location='cpu') |
||||
log = model.load_state_dict(clean_state_dict(checkpoint['model']), strict=False) |
||||
print("Model loaded from {} \n => {}".format(cache_file, log)) |
||||
_ = model.eval() |
||||
return model |
||||
|
||||
def image_transform_grounding(init_image): |
||||
transform = T.Compose([ |
||||
T.RandomResize([800], max_size=1333), |
||||
T.ToTensor(), |
||||
T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]) |
||||
]) |
||||
image, _ = transform(init_image, None) # 3, h, w |
||||
return init_image, image |
||||
|
||||
def image_transform_grounding_for_vis(init_image): |
||||
transform = T.Compose([ |
||||
T.RandomResize([800], max_size=1333), |
||||
]) |
||||
image, _ = transform(init_image, None) # 3, h, w |
||||
return image |
||||
|
||||
model = load_model_hf(config_file, ckpt_repo_id, ckpt_filenmae) |
||||
|
||||
def run_grounding(input_image, grounding_caption, box_threshold, text_threshold): |
||||
init_image = input_image.convert("RGB") |
||||
original_size = init_image.size |
||||
|
||||
_, image_tensor = image_transform_grounding(init_image) |
||||
image_pil: Image = image_transform_grounding_for_vis(init_image) |
||||
|
||||
# run grounidng |
||||
boxes, logits, phrases = predict(model, image_tensor, grounding_caption, box_threshold, text_threshold, device='cpu') |
||||
annotated_frame = annotate(image_source=np.asarray(image_pil), boxes=boxes, logits=logits, phrases=phrases) |
||||
image_with_box = Image.fromarray(cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)) |
||||
|
||||
|
||||
return image_with_box |
||||
|
||||
if __name__ == "__main__": |
||||
|
||||
parser = argparse.ArgumentParser("Grounding DINO demo", add_help=True) |
||||
parser.add_argument("--debug", action="store_true", help="using debug mode") |
||||
parser.add_argument("--share", action="store_true", help="share the app") |
||||
args = parser.parse_args() |
||||
|
||||
block = gr.Blocks().queue() |
||||
with block: |
||||
gr.Markdown("# [Grounding DINO](https://github.com/IDEA-Research/GroundingDINO)") |
||||
gr.Markdown("### Open-World Detection with Grounding DINO") |
||||
|
||||
with gr.Row(): |
||||
with gr.Column(): |
||||
input_image = gr.Image(source='upload', type="pil") |
||||
grounding_caption = gr.Textbox(label="Detection Prompt") |
||||
run_button = gr.Button(label="Run") |
||||
with gr.Accordion("Advanced options", open=False): |
||||
box_threshold = gr.Slider( |
||||
label="Box Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.001 |
||||
) |
||||
text_threshold = gr.Slider( |
||||
label="Text Threshold", minimum=0.0, maximum=1.0, value=0.25, step=0.001 |
||||
) |
||||
|
||||
with gr.Column(): |
||||
gallery = gr.outputs.Image( |
||||
type="pil", |
||||
# label="grounding results" |
||||
).style(full_width=True, full_height=True) |
||||
# gallery = gr.Gallery(label="Generated images", show_label=False).style( |
||||
# grid=[1], height="auto", container=True, full_width=True, full_height=True) |
||||
|
||||
run_button.click(fn=run_grounding, inputs=[ |
||||
input_image, grounding_caption, box_threshold, text_threshold], outputs=[gallery]) |
||||
|
||||
|
||||
block.launch(server_name='0.0.0.0', server_port=7579, debug=args.debug, share=args.share) |
||||
|
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -1,43 +0,0 @@ |
||||
batch_size = 1 |
||||
modelname = "groundingdino" |
||||
backbone = "swin_B_384_22k" |
||||
position_embedding = "sine" |
||||
pe_temperatureH = 20 |
||||
pe_temperatureW = 20 |
||||
return_interm_indices = [1, 2, 3] |
||||
backbone_freeze_keywords = None |
||||
enc_layers = 6 |
||||
dec_layers = 6 |
||||
pre_norm = False |
||||
dim_feedforward = 2048 |
||||
hidden_dim = 256 |
||||
dropout = 0.0 |
||||
nheads = 8 |
||||
num_queries = 900 |
||||
query_dim = 4 |
||||
num_patterns = 0 |
||||
num_feature_levels = 4 |
||||
enc_n_points = 4 |
||||
dec_n_points = 4 |
||||
two_stage_type = "standard" |
||||
two_stage_bbox_embed_share = False |
||||
two_stage_class_embed_share = False |
||||
transformer_activation = "relu" |
||||
dec_pred_bbox_embed_share = True |
||||
dn_box_noise_scale = 1.0 |
||||
dn_label_noise_ratio = 0.5 |
||||
dn_label_coef = 1.0 |
||||
dn_bbox_coef = 1.0 |
||||
embed_init_tgt = True |
||||
dn_labelbook_size = 2000 |
||||
max_text_len = 256 |
||||
text_encoder_type = "bert-base-uncased" |
||||
use_text_enhancer = True |
||||
use_fusion_layer = True |
||||
use_checkpoint = True |
||||
use_transformer_ckpt = True |
||||
use_text_cross_attention = True |
||||
text_dropout = 0.0 |
||||
fusion_dropout = 0.0 |
||||
fusion_droppath = 0.1 |
||||
sub_sentence_present = True |
Loading…
Reference in new issue