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import gradio as gr |
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from paths import * |
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from vision_tower import DINOv2_MLP |
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from transformers import AutoImageProcessor |
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import torch |
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from inference import * |
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from utils import * |
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from huggingface_hub import hf_hub_download |
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ckpt_path = hf_hub_download(repo_id="Viglong/Orient-Anything", filename="ronormsigma1/dino_weight.pt", repo_type="model", cache_dir='./', resume_download=True) |
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print(ckpt_path) |
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save_path = './' |
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device = 'cpu' |
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dino = DINOv2_MLP( |
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dino_mode = 'large', |
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in_dim = 1024, |
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out_dim = 360+180+360+2, |
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evaluate = True, |
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mask_dino = False, |
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frozen_back = False |
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) |
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dino.eval() |
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print('model create') |
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dino.load_state_dict(torch.load(ckpt_path, map_location='cpu')) |
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dino = dino.to(device) |
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print('weight loaded') |
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val_preprocess = AutoImageProcessor.from_pretrained(DINO_LARGE, cache_dir='./') |
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def infer_func(img, do_rm_bkg, do_infer_aug): |
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origin_img = Image.fromarray(img) |
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if do_infer_aug: |
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rm_bkg_img = background_preprocess(origin_img, True) |
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angles = get_3angle_infer_aug(origin_img, rm_bkg_img, dino, val_preprocess, device) |
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else: |
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rm_bkg_img = background_preprocess(origin_img, do_rm_bkg) |
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angles = get_3angle(rm_bkg_img, dino, val_preprocess, device) |
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phi = np.radians(angles[0]) |
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theta = np.radians(angles[1]) |
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gamma = angles[2] |
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confidence = float(angles[3]) |
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if confidence > 0.5: |
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render_axis = render_3D_axis(phi, theta, gamma) |
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res_img = overlay_images_with_scaling(render_axis, rm_bkg_img) |
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else: |
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res_img = img |
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return [res_img, round(float(angles[0]), 2), round(float(angles[1]), 2), round(float(angles[2]), 2), round(float(angles[3]), 2)] |
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server = gr.Interface( |
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flagging_mode='never', |
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fn=infer_func, |
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inputs=[ |
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gr.Image(height=512, width=512, label="upload your image"), |
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gr.Checkbox(label="Remove Background", value=True), |
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gr.Checkbox(label="Inference time augmentation", value=False) |
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], |
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outputs=[ |
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gr.Image(height=512, width=512, label="result image"), |
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gr.Textbox(lines=1, label='Azimuth(0~360°)'), |
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gr.Textbox(lines=1, label='Polar(-90~90°)'), |
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gr.Textbox(lines=1, label='Rotation(-90~90°)'), |
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gr.Textbox(lines=1, label='Confidence(0~1)') |
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] |
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) |
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server.launch() |
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