[update] update finegrasp_pipeline_sim and README

README.md

@@ -35,19 +35,67 @@ license: apache-2.0
 </div>
 
 
-# Grasp performance in GraspNet-1Billion dataset.
+## 1. Grasp performance in GraspNet-1Billion dataset.
 
 | Method    | ckpt | Camera    | Seen (AP) | Similar (AP) | Novel (AP) | Average (AP) |
 | --------- | ---- | --------- | --------- | ------------ | ---------- | ---------- |
-| FineGrasp | finegrasp_wo_sim.pth | Realsense | 71.67     | 62.83        | 27.40      | 53.97 |
-| FineGrasp + CD | finegrasp_wo_sim.pth |  Realsense | 73.71 | 64.56 | 28.14 | 55.47 |
-| FineGrasp + Simulation Data | finegrasp_sim.pth |  Realsense | 70.21 | 61.98 | 26.18 | 52.79 |
+| FineGrasp | finegrasp_pipeline/model.safetensors | Realsense | 71.67     | 62.83        | 27.40      | 53.97 |
+| FineGrasp + CD | finegrasp_pipeline/model.safetensors |  Realsense | 73.71 | 64.56 | 28.14 | 55.47 |
+| FineGrasp + Simulation Data | finegrasp_pipeline_sim/model.safetensors |  Realsense | 70.21 | 61.98 | 26.18 | 52.79 |
 
 
 We also provide a grasp-based baseline for [Challenge Cup](https://developer.d-robotics.cc/tiaozhanbei-2025), please refer to this [code](https://github.com/HorizonRobotics/robo_orchard_lab/tree/master/projects/pick_place_agent)
-> Notice: finegrasp_sim.pth is trained for [Challenge Cup](https://developer.d-robotics.cc/tiaozhanbei-2025) RoboTwin simulation benchmark.
+> Notice: finegrasp_pipeline_sim/model.safetensors is trained for [Challenge Cup](https://developer.d-robotics.cc/tiaozhanbei-2025) RoboTwin simulation benchmark.
 
-# Citation
+
+## 2. Example Infer Code
+```Python
+import os
+import numpy as np
+import scipy.io as scio
+from PIL import Image
+from robo_orchard_lab.models.finegrasp.processor import GraspInput
+from huggingface_hub import snapshot_download
+from robo_orchard_lab.inference import InferencePipelineMixin
+
+file_path = snapshot_download(
+    repo_id="HorizonRobotics/FineGrasp",
+    allow_patterns=[
+        "finegrasp_pipeline/**",
+        "data_example/**"
+    ],  
+)
+
+loaded_pipeline = InferencePipelineMixin.load(
+    os.path.join(file_path, "finegrasp_pipeline")
+)
+
+rgb_image_path = os.path.join(file_path, "data_example/0000_rgb.png")
+depth_image_path = os.path.join(file_path, "data_example/0000_depth.png")
+intrinsic_file = os.path.join(file_path, "data_example/0000.mat")
+
+depth_image = np.array(Image.open(depth_image_path), dtype=np.float32)
+rgb_image = np.array(Image.open(rgb_image_path), dtype=np.float32) / 255.0
+intrinsic_matrix = scio.loadmat(intrinsic_file)["intrinsic_matrix"]
+workspace = [-1, 1, -1, 1, 0.0, 2.0]
+depth_scale = 1000.0
+
+input_data = GraspInput(
+    rgb_image=rgb_image,
+    depth_image=depth_image,
+    depth_scale=depth_scale,
+    intrinsic_matrix=intrinsic_matrix,
+    workspace=workspace,
+)
+
+loaded_pipeline.to("cuda")
+loaded_pipeline.model.eval()
+output = loaded_pipeline(input_data)
+print(f"Best grasp pose: {output.grasp_poses[0]}")
+
+```
+
+## Citation
 ```
 @misc{du2025finegrasp,
     title={FineGrasp: Towards Robust Grasping for Delicate Objects}, 

finegrasp_pipeline_sim/inference.config.json

@@ -0,0 +1,17 @@
+{
+    "__config_type__": "robo_orchard_lab.inference.basic:InferencePipelineCfg",
+    "class_type": "robo_orchard_lab.inference.basic:InferencePipeline",
+    "model": null,
+    "processor": {
+        "__config_type__": "robo_orchard_lab.models.finegrasp.processor:FineGraspProcessorCfg",
+        "class_type": "robo_orchard_lab.models.finegrasp.processor:FineGraspProcessor",
+        "voxel_size": 0.005,
+        "grasp_max_width": 0.1,
+        "num_seed_points": 1024,
+        "max_gripper_width": 0.1,
+        "collision_thresh": 0.01,
+        "voxel_size_cd": 0.01
+    },
+    "collate_fn": null,
+    "batch_size": 1
+}

model.config.json → finegrasp_pipeline_sim/model.config.json

@@ -17,6 +17,6 @@
         0.75,
         1.0
     ],
-    "use_normal": true,
+    "use_normal": false,
     "loss": null
 }

model.safetensors → finegrasp_pipeline_sim/model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:8b27b2f0a3a3b40e66fa7a631c7a53c2e56bf4cb928f1cce1360bb6203a6b368
+size 76646428

finegrasp_processor.json

@@ -1,10 +0,0 @@
-{
-    "__config_type__": "robo_orchard_lab.models.finegrasp.processor:FineGraspProcessorCfg",
-    "class_type": "robo_orchard_lab.models.finegrasp.processor:FineGraspProcessor",
-    "voxel_size": 0.005,
-    "grasp_max_width": 0.1,
-    "num_seed_points": 1024,
-    "max_gripper_width": 0.1,
-    "collision_thresh": 0.01,
-    "voxel_size_cd": 0.01
-}

finegrasp_sim.pth

@@ -1,3 +0,0 @@
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-size 230029850

finegrasp_wo_sim.pth

@@ -1,3 +0,0 @@
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