Add minimal usage snippets (Kotlin + Python)

README.md

@@ -43,6 +43,49 @@ GPU-clean. Result: banned ops NONE, all tensors ≤4D, tflite-vs-torch corr **1.
 Resize to 512×512, append a 4th channel of ones, scale `(x/127.5) - 1`, NCHW. Decode: sigmoid the center map,
 3×3 max NMS, threshold (0.10), displacement → endpoints, filter by length, ×2 to 512-space.
 
+## Minimal usage
+
+**Android (Kotlin, CompiledModel GPU)**
+
+```kotlin
+val model = CompiledModel.create(context.assets, "mlsd_fp16.tflite",
+    CompiledModel.Options(Accelerator.GPU), null)
+val inputs = model.createInputBuffers(); val outputs = model.createOutputBuffers()
+inputs[0].writeFloat(x)             // [1,4,512,512] NCHW: RGB + ones channel, x/127.5 - 1
+model.run(inputs, outputs)
+val tpMap = outputs[0].readFloat()  // [1,9,256,256]: ch0 center, ch1-4 displacement
+// sigmoid + 3x3 NMS + displacement -> segments: port of the Python decode below.
+```
+
+**Python (desktop verification)**
+
+```python
+import numpy as np
+from PIL import Image
+from scipy.ndimage import maximum_filter
+from ai_edge_litert.interpreter import Interpreter
+
+im = Image.open("photo.jpg").convert("RGB").resize((512, 512))
+a = np.asarray(im, np.float32)
+a = np.concatenate([a, np.ones((512, 512, 1), np.float32)], -1)   # 4th channel of ones
+x = ((a.transpose(2, 0, 1)[None] / 127.5) - 1.0).copy()           # [1,4,512,512]
+
+it = Interpreter(model_path="mlsd_fp16.tflite"); it.allocate_tensors()
+it.set_tensor(it.get_input_details()[0]["index"], x); it.invoke()
+tp = it.get_tensor(it.get_output_details()[0]["index"])[0]        # [9,256,256]
+
+center = 1 / (1 + np.exp(-tp[0])); disp = tp[1:5]
+peak = (center == maximum_filter(center, 3)) & (center > 0.10)    # 3x3 NMS + threshold
+ys, xs = np.where(peak)
+order = center[ys, xs].argsort()[::-1][:200]                      # top-200 centers
+lines = []
+for y, x0 in zip(ys[order], xs[order]):
+    dxs, dys, dxe, dye = disp[:, y, x0]
+    if np.hypot(dxs - dxe, dys - dye) > 20:                       # min segment length (px)
+        lines.append([(x0 + dxs) * 2, (y + dys) * 2, (x0 + dxe) * 2, (y + dye) * 2])
+print(f"{len(lines)} line segments (x0,y0,x1,y1 in 512-space)")
+```
+
 ## License
 
 [Apache-2.0](https://github.com/navervision/mlsd/blob/main/LICENSE). Upstream: