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告别繁琐训练!用 Python + ONNX Runtime 轻松部署 INSID3,开启零样本图像分割新时代

  • 2026-06-28 18:42:49
告别繁琐训练!用 Python + ONNX Runtime 轻松部署 INSID3,开启零样本图像分割新时代

说明

官网地址:https://github.com/visinf/INSID3

在计算机视觉领域,图像分割一直是一项极具挑战性的任务。传统方法往往需要大量标注数据、长时间模型训练,以及针对不同物体类别的反复微调。但今天,这一切将被彻底改变——INSID3 横空出世,它以一种全新的 In-Context(上下文学习) 范式,让你仅需提供一张参考图像和其掩码,就能在任意目标图像中精准分割出同款物体,完全无需任何训练!

更令人兴奋的是,通过 ONNX Runtime 的加持,我们可以将 INSID3 高效地部署 到生产环境中,实现跨平台、跨语言的高性能推理。本文将从零开始,带你了解 INSID3 的原理、优势,并手把手教你如何使用 Python + ONNX Runtime 快速部署 INSID3,让你轻松拥有一次标注、处处分割的“超能力”。

INSID3(In-context Segmentation with a Non‑trainable DINOv3 encoder)是一种无需训练的分割模型,它的核心思想非常简单:

利用一个冻结的大型视觉编码器(DINOv3)提取图像特征,然后通过巧妙的特征匹配和聚类机制,将参考物体的语义“传递”到目标图像上。

换句话说,你只需要在参考图上勾画或选择一个物体,INSID3 就能自动在其他图像中找到同样的物体,并生成精确的分割掩码。整个过程没有训练、没有梯度下降、不依赖特定类别,真正做到了开箱即用、万物皆可分割。

效果

模型信息

Model Properties----------------------------------------------------------------------------------------Inputs-------------------------name:imgstensor:Float[-1, 3, 1024, 1024]---------------------------------------------------------------Outputs-------------------------name:f_normtensor:Float[-1, 1024, 64, 64]name:f_debiastensor:Float[-1, 1024, 64, 64]---------------------------------------------------------------

代码

class INSID3App:    def __init__(self, root, onnx_path="insid3_encoder_nobatch.onnx"):        self.root = root        self.root.title("INSID3 交互式分割")        self.onnx_path = onnx_path        self.ref_orig = None        self.tgt_orig = None        self.ref_disp = None        self.tgt_disp = None        self.mask_np = None        self.mask_pil = None        self.result = None        self.display_size = 500        self.points = []        self.cached_model = None        self._build_ui()    def _build_ui(self):        toolbar = tk.Frame(self.root)        toolbar.pack(side=tk.TOP, fill=tk.X, padx=5, pady=5)for text, cmd in [("加载参考图", self.load_ref), ("加载目标图", self.load_tgt),                          ("清除多边形", self.clear_poly), ("生成掩码", self.gen_mask),                          ("缓存参考", self.cache_ref), ("推理", self.run_inference),                          ("保存结果", self.save_result)]:            tk.Button(toolbar, text=text, command=cmd).pack(side=tk.LEFT, padx=2)        self.info_var = tk.StringVar(value="选点: 0")        tk.Label(toolbar, textvariable=self.info_var).pack(side=tk.LEFT, padx=10)        cf = tk.Frame(self.root); cf.pack(fill=tk.BOTH, expand=True)        self.cv_ref = tk.Canvas(cf, width=self.display_size, height=self.display_size,bg='gray', cursor="cross")        self.cv_ref.grid(row=0, column=0, padx=5)        tk.Label(cf, text="参考图 (左键加点 / 右键删点)").grid(row=1, column=0)        self.cv_tgt = tk.Canvas(cf, width=self.display_size, height=self.display_size, bg='gray')        self.cv_tgt.grid(row=0, column=1, padx=5)        tk.Label(cf, text="目标图").grid(row=1, column=1)        self.cv_res = tk.Canvas(cf, width=self.display_size, height=self.display_size, bg='gray')        self.cv_res.grid(row=0, column=2, padx=5)        tk.Label(cf, text="分割结果").grid(row=1, column=2)        self.cv_ref.bind("<Button-1>", self.add_point)        self.cv_ref.bind("<Button-3>", self.rm_last)        self.prog = ttk.Progressbar(self.root, mode='indeterminate')        self.prog.pack(fill=tk.X)        self.stvar = tk.StringVar(value="就绪")        tk.Label(self.root, textvariable=self.stvar, bd=1, relief=tk.SUNKEN, anchor=tk.W).pack(fill=tk.X)    def load_ref(self):        path = filedialog.askopenfilename(filetypes=[("Image""*.jpg *.jpeg *.png *.bmp")])if not path: return        self.ref_orig = Image.open(path).convert("RGB")        self.ref_disp, _ = letterbox_image(self.ref_orig, self.display_size)        self.points.clear(); self.mask_np = None; self.cached_model = None        self._redraw(); self.stvar.set(f"参考: {path}")    def _redraw(self):if self.ref_disp is None: return        base = self.ref_disp.copy().convert("RGBA")if self.mask_np is not None and self.mask_np.sum() > 0:            base = self._overlay(base, self.mask_np)        draw = ImageDraw.Draw(base)for x,y in self.points:            r = 4; draw.ellipse((x-r, y-r, x+r, y+r), fill='green')if len(self.points) > 1:            draw.line(self.points, fill='yellow', width=2)        self.ref_tk = ImageTk.PhotoImage(base)        self.cv_ref.delete("all"); self.cv_ref.create_image(0,0,anchor=tk.NW, image=self.ref_tk)        self.info_var.set(f"选点:{len(self.points)}")    def _overlay(self, base, mask_1024):        small = Image.fromarray(mask_1024).resize((self.display_size, self.display_size), Image.NEAREST)        ov = Image.new("RGBA", (self.display_size, self.display_size), (0,0,0,0))for y in range(self.display_size):for x in range(self.display_size):if small.getpixel((x,y)) > 128: ov.putpixel((x,y), (255,0,0,100))return Image.alpha_composite(base, ov)    def load_tgt(self):        path = filedialog.askopenfilename(filetypes=[("Image""*.jpg *.jpeg *.png *.bmp")])if not path: return        self.tgt_orig = Image.open(path).convert("RGB")        self.tgt_disp, _ = letterbox_image(self.tgt_orig, self.display_size)        self.tgt_tk = ImageTk.PhotoImage(self.tgt_disp)        self.cv_tgt.delete("all"); self.cv_tgt.create_image(0,0,anchor=tk.NW, image=self.tgt_tk)        self.stvar.set(f"目标: {path}")    def add_point(self, event): self.points.append((event.x, event.y)); self._redraw()    def rm_last(self, event):if self.points: self.points.pop(); self._redraw()    def clear_poly(self): self.points.clear(); self._redraw()    def gen_mask(self):if len(self.points) < 3: messagebox.showwarning("警告""至少需要3个顶点"); return        scale_x = 1024 / self.display_size        scale_y = 1024 / self.display_size        pts = [(int(x*scale_x), int(y*scale_y)) for x,y in self.points]        mask = np.zeros((1024,1024), dtype=np.uint8)        cv2.fillPoly(mask, [np.array(pts, dtype=np.int32)], 255)        self.mask_np = mask        self.mask_pil = Image.fromarray(mask, 'L')        self._redraw(); self.stvar.set("掩码已生成")    def cache_ref(self):if self.ref_orig is None or self.mask_pil is None:            messagebox.showwarning("缺少数据""请先加载参考图并生成掩码"); return        try:            self.cached_model = OnnxINSID3(self.onnx_path, device='cuda')            self.cached_model.encode_reference(self.ref_orig, self.mask_pil)            self.stvar.set("参考特征已缓存,可连续推理")        except Exception as e: messagebox.showerror("缓存失败", str(e))    def run_inference(self):if self.ref_orig is None or self.mask_pil is None or self.tgt_orig is None:            messagebox.showwarning("缺少数据""请加载参考图、掩码和目标图"); return        self.cv_res.delete("all"); self.prog.start(); self.stvar.set("推理中...")        threading.Thread(target=self._inf, daemon=True).start()    def _inf(self):        start = time.time()        try:if self.cached_model and self.cached_model._cached_ref_norm is not None:                result_pil = self.cached_model.segment_with_cache(self.tgt_orig)else:                model = OnnxINSID3(self.onnx_path, device='cuda')                model.set_reference(self.ref_orig, self.mask_pil)                model.set_target(self.tgt_orig)                result_pil = model.segment()            self.result = result_pil            elapsed = time.time() - start            self.root.after(0, self._show)            self.root.after(0, lambda e=elapsed: self.stvar.set(f"完成,耗时 {e:.2f}s"))        except Exception as e:            self.root.after(0, lambda e=e: messagebox.showerror("推理错误", str(e)))        finally:            self.root.after(0, self.prog.stop)    def _show(self):if self.result is None: return        tgt_disp = self.tgt_orig.resize((self.display_size, self.display_size))        res_disp = self.result.resize((self.display_size, self.display_size))        base = tgt_disp.convert("RGBA")        ov = Image.new("RGBA", (self.display_size, self.display_size), (0,0,0,0))        arr = np.array(res_disp) > 128for y in range(self.display_size):for x in range(self.display_size):if arr[y,x]: ov.putpixel((x,y), (255,0,0,100))        base = Image.alpha_composite(base, ov)        self.res_tk = ImageTk.PhotoImage(base)        self.cv_res.delete("all"); self.cv_res.create_image(0,0,anchor=tk.NW, image=self.res_tk)    def save_result(self):if self.result is None: messagebox.showwarning("无结果""请先推理"); return        path = filedialog.asksaveasfilename(defaultextension=".png", filetypes=[("PNG""*.png")])if path: self.result.save(path); messagebox.showinfo("保存成功", f"已保存至 {path}")if __name__ == "__main__":    root = tk.Tk()# app = INSID3App(root, onnx_path="insid3_encoder_nobatch.onnx")    app = INSID3App(root, onnx_path="insid3_encoder_nobatch_simplified.onnx")    root.mainloop()

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  1. CONNECT:[ UseTime:0.001164s ] mysql:host=127.0.0.1;port=3306;dbname=f_mffb;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `fenlei` [ RunTime:0.001678s ]
  3. SELECT * FROM `fenlei` WHERE `fid` = 0 [ RunTime:0.000729s ]
  4. SELECT * FROM `fenlei` WHERE `fid` = 63 [ RunTime:0.000671s ]
  5. SHOW FULL COLUMNS FROM `set` [ RunTime:0.001355s ]
  6. SELECT * FROM `set` [ RunTime:0.000521s ]
  7. SHOW FULL COLUMNS FROM `article` [ RunTime:0.001482s ]
  8. SELECT * FROM `article` WHERE `id` = 490718 LIMIT 1 [ RunTime:0.001089s ]
  9. UPDATE `article` SET `lasttime` = 1783063303 WHERE `id` = 490718 [ RunTime:0.009091s ]
  10. SELECT * FROM `fenlei` WHERE `id` = 66 LIMIT 1 [ RunTime:0.003290s ]
  11. SELECT * FROM `article` WHERE `id` < 490718 ORDER BY `id` DESC LIMIT 1 [ RunTime:0.001193s ]
  12. SELECT * FROM `article` WHERE `id` > 490718 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.001002s ]
  13. SELECT * FROM `article` WHERE `id` < 490718 ORDER BY `id` DESC LIMIT 10 [ RunTime:0.002159s ]
  14. SELECT * FROM `article` WHERE `id` < 490718 ORDER BY `id` DESC LIMIT 10,10 [ RunTime:0.002274s ]
  15. SELECT * FROM `article` WHERE `id` < 490718 ORDER BY `id` DESC LIMIT 20,10 [ RunTime:0.002211s ]
0.217828s