Create app.py

app.py

@@ -0,0 +1,363 @@
+import gradio as gr
+from huggingface_hub import HfApi
+
+def build_teleop_command(
+    robot_type,
+    robot_port,
+    robot_id,
+    cam_index,
+    cam_width,
+    cam_height,
+    cam_fps,
+    teleop_type,
+    teleop_port,
+    teleop_id,
+    fps,
+    teleop_duration,
+    display_data,
+):
+    cam_cfg = (
+        "{ front: {type: opencv, index_or_path: %d, width: %d, height: %d, fps: %d}}"
+        % (cam_index, cam_width, cam_height, cam_fps)
+    )
+
+    cmd = [
+        "python -m lerobot.teleoperate",
+        f"--robot.type={robot_type}",
+        f"--robot.port={robot_port}",
+        f"--robot.id={robot_id}",
+        f"--robot.cameras=\"{cam_cfg}\"",
+        f"--teleop.type={teleop_type}",
+        f"--teleop.port={teleop_port}",
+        f"--teleop.id={teleop_id}",
+        f"--fps={fps}",
+    ]
+    if teleop_duration:
+        cmd.append(f"--teleop_time_s={teleop_duration}")
+    cmd.append(f"--display_data={'true' if display_data else 'false'}")
+    return " \\\n    ".join(cmd)
+
+
+def build_record_command(
+    robot_type,
+    robot_port,
+    robot_id,
+    cam_index,
+    cam_width,
+    cam_height,
+    cam_fps,
+    teleop_type,
+    teleop_port,
+    teleop_id,
+    display_data,
+    dataset_repo,
+    num_episodes,
+    single_task,
+    resume,
+    push_to_hub,
+    use_existing,
+    existing_ds,
+):
+    # if using existing dataset, override dataset_repo
+    if use_existing and existing_ds:
+        dataset_repo = existing_ds
+
+    camera_cfg = (
+        "{ front: {type: opencv, index_or_path: %d, width: %d, height: %d, fps: %d}}"
+        % (cam_index, cam_width, cam_height, cam_fps)
+    )
+    cmd = [
+        "python -m lerobot.record",
+        f"--robot.type={robot_type}",
+        f"--robot.port={robot_port}",
+        f"--robot.id={robot_id}",
+        f"--robot.cameras=\"{camera_cfg}\"",
+        f"--teleop.type={teleop_type}",
+        f"--teleop.port={teleop_port}",
+        f"--teleop.id={teleop_id}",
+        f"--display_data={'true' if display_data else 'false'}",
+        f"--dataset.repo_id={dataset_repo}",
+        f"--dataset.num_episodes={num_episodes}",
+        f"--dataset.single_task=\"{single_task}\"",
+    ]
+    cmd.append(f"--dataset.push_to_hub={'true' if push_to_hub else 'false'}")
+    if resume:
+        cmd.append("--resume=True")
+    return " \\\n    ".join(cmd)
+
+
+def build_train_command(
+    policy_path,
+    dataset_repo,
+    batch_size,
+    steps,
+    output_dir,
+    job_name,
+    device,
+    wandb_enable,
+    policy_repo_id,
+):
+    cmd = [
+        "python -m lerobot.scripts.train",
+        f"--policy.path={policy_path}",
+        f"--dataset.repo_id={dataset_repo}",
+        f"--batch_size={batch_size}",
+        f"--steps={steps}",
+        f"--output_dir={output_dir}",
+        f"--job_name={job_name}",
+        f"--policy.device={device}",
+        f"--wandb.enable={'true' if wandb_enable else 'false'}",
+        f"--policy.repo_id={policy_repo_id}" if policy_repo_id else "",
+    ]
+    # filter empty strings
+    cmd = [c for c in cmd if c]
+    return " \\\n    ".join(cmd)
+
+
+def build_eval_command(
+    robot_type,
+    robot_port,
+    robot_id,
+    cam_index,
+    cam_width,
+    cam_height,
+    cam_fps,
+    display_data,
+    dataset_repo,
+    num_episodes,
+    single_task,
+    policy_path,
+    resume,
+):
+    camera_cfg = (
+        "{ front: {type: opencv, index_or_path: %d, width: %d, height: %d, fps: %d}}"
+        % (cam_index, cam_width, cam_height, cam_fps)
+    )
+
+    cmd = [
+        "python -m lerobot.record",
+        f"--robot.type={robot_type}",
+        f"--robot.port={robot_port}",
+        f"--robot.id={robot_id}",
+        f"--robot.cameras=\"{camera_cfg}\"",
+        f"--display_data={'true' if display_data else 'false'}",
+        f"--dataset.repo_id={dataset_repo}",
+        f"--dataset.num_episodes={num_episodes}",
+        f"--dataset.single_task=\"{single_task}\"",
+        f"--policy.path={policy_path}",
+    ]
+    if resume:
+        cmd.append("--resume=True")
+    return " \\\n    ".join(cmd)
+
+
+# Helper to list datasets on Hugging Face for given username
+def _list_remote_datasets(username: str):
+    try:
+        api = HfApi()
+        datasets = api.list_datasets(author=username)
+        return sorted([d.id for d in datasets])
+    except Exception:
+        return []
+
+
+def build_ui():
+    with gr.Blocks(title="Lerobot Scripts Controller (Generate Only)") as demo:
+        hf_username_tb = gr.Textbox(label="HF Username", value="arpitg1304")
+        with gr.Tabs():
+            # Teleoperate Tab
+            with gr.TabItem("Teleoperate Robot"):
+                gr.Markdown("### Teleoperate robot with camera")
+                with gr.Row():
+                    robot_type = gr.Textbox(label="Robot Type", value="so101_follower")
+                    robot_port = gr.Textbox(label="Robot Port", value="/dev/ttyACM0")
+                    robot_id = gr.Textbox(label="Robot ID", value="follower")
+                with gr.Row():
+                    cam_index = gr.Number(label="Cam Index", value=0, precision=0)
+                    cam_width = gr.Number(label="Width", value=640, precision=0)
+                    cam_height = gr.Number(label="Height", value=480, precision=0)
+                    cam_fps = gr.Number(label="FPS", value=30, precision=0)
+                with gr.Row():
+                    teleop_type = gr.Textbox(label="Teleop Type", value="so101_leader")
+                    teleop_port = gr.Textbox(label="Teleop Port", value="/dev/ttyACM1")
+                    teleop_id = gr.Textbox(label="Teleop ID", value="leader")
+                with gr.Row():
+                    fps = gr.Number(label="Loop FPS", value=60, precision=0)
+                    teleop_duration = gr.Number(label="Duration (s)", value=60, precision=0)
+                    display_data = gr.Checkbox(label="Display Data", value=True)
+                teleop_cmd = gr.Textbox(label="Generated Command", interactive=False, lines=16)
+
+                inputs_teleop = [
+                    robot_type,
+                    robot_port,
+                    robot_id,
+                    cam_index,
+                    cam_width,
+                    cam_height,
+                    cam_fps,
+                    teleop_type,
+                    teleop_port,
+                    teleop_id,
+                    fps,
+                    teleop_duration,
+                    display_data,
+                ]
+                gr.Button("Generate Command").click(build_teleop_command, inputs_teleop, outputs=teleop_cmd)
+
+            # Record Data Tab
+            with gr.TabItem("Record Data"):
+                gr.Markdown("### Record episodes with policy")
+                with gr.Row():
+                    robot_type2 = gr.Textbox(label="Robot Type", value="so101_follower")
+                    robot_port2 = gr.Textbox(label="Robot Port", value="/dev/ttyACM0")
+                    robot_id2 = gr.Textbox(label="Robot ID", value="follower")
+                with gr.Row():
+                    cam_index2 = gr.Number(label="Cam Index", value=0, precision=0)
+                    cam_width2 = gr.Number(label="Width", value=640, precision=0)
+                    cam_height2 = gr.Number(label="Height", value=480, precision=0)
+                    cam_fps2 = gr.Number(label="FPS", value=30, precision=0)
+                with gr.Row():
+                    teleop_type_r = gr.Textbox(label="Teleop Type", value="so101_leader")
+                    teleop_port_r = gr.Textbox(label="Teleop Port", value="/dev/ttyACM1")
+                    teleop_id_r = gr.Textbox(label="Teleop ID", value="leader")
+                with gr.Row():
+                    display_data2 = gr.Checkbox(label="Display Data", value=True)
+                    dataset_repo = gr.Textbox(label="Dataset Repo", value="")
+                    num_episodes = gr.Number(label="Num Episodes", value=2, precision=0)
+                    single_task = gr.Textbox(label="Single Task", value="Grab the cylinder")
+                    resume_chk = gr.Checkbox(label="Resume", value=False)
+                    push_hub_chk = gr.Checkbox(label="Push to Hub", value=False)
+                with gr.Row():
+                    use_existing = gr.Checkbox(label="Use Existing Dataset", value=False)
+                    existing_dd = gr.Dropdown(label="User Datasets", choices=_list_remote_datasets(hf_username_tb.value), visible=False)
+                # Toggle dropdown visibility
+                use_existing.change(lambda f: gr.update(visible=f), inputs=use_existing, outputs=existing_dd)
+
+                # Update dataset choices when username changes
+                def _update_ds_choices(username):
+                    return gr.update(choices=_list_remote_datasets(username))
+
+                hf_username_tb.change(_update_ds_choices, inputs=hf_username_tb, outputs=existing_dd)
+
+                record_cmd = gr.Textbox(label="Generated Command", interactive=False, lines=16)
+                inputs_rec = [
+                    robot_type2,
+                    robot_port2,
+                    robot_id2,
+                    cam_index2,
+                    cam_width2,
+                    cam_height2,
+                    cam_fps2,
+                    teleop_type_r,
+                    teleop_port_r,
+                    teleop_id_r,
+                    display_data2,
+                    dataset_repo,
+                    num_episodes,
+                    single_task,
+                    resume_chk,
+                    push_hub_chk,
+                    use_existing,
+                    existing_dd,
+                ]
+                gr.Button("Generate Command").click(build_record_command, inputs_rec, record_cmd)
+
+            # Train Policy Tab
+            with gr.TabItem("Train Policy"):
+                gr.Markdown("### Train Policy")
+                # Row 1: Policy path (full width)
+                policy_path_t = gr.Textbox(label="Base Policy Path", value="lerobot/smolvla_base")
+
+                # Row 2: Dataset + Device + WandB enable
+                with gr.Row():
+                    dataset_repo_t = gr.Dropdown(
+                        label="User Dataset",
+                        choices=_list_remote_datasets(hf_username_tb.value),
+                        scale=4,
+                    )
+                    device_t = gr.Dropdown(label="Device", choices=["cpu", "cuda"], value="cuda", scale=1)
+                    wandb_chk = gr.Checkbox(label="W&B", value=True, scale=1)
+
+                # Row 3: Batch size & Steps
+                with gr.Row():
+                    batch_size_t = gr.Number(label="Batch Size", value=16, precision=0, scale=1)
+                    steps_t = gr.Number(label="Steps", value=20000, precision=0, scale=1)
+
+                # Row 4: Output dir (full width)
+                output_dir_t = gr.Textbox(label="Output Dir", value="outputs/train/my_smolvla_1")
+
+                # Row 5: Job name & Policy repo id
+                with gr.Row():
+                    job_name_t = gr.Textbox(label="Job Name", value="smolvla_place_cylinder", scale=1)
+                    policy_repo_t = gr.Textbox(label="Policy Repo ID (optional)", value="", scale=1)
+
+                # Update train dataset dropdown when username changes
+                hf_username_tb.change(_update_ds_choices, inputs=hf_username_tb, outputs=dataset_repo_t)
+
+                train_cmd = gr.Textbox(label="Generated Command", interactive=False, lines=16)
+                gr.Button("Generate Command").click(
+                    build_train_command,
+                    [
+                        policy_path_t,
+                        dataset_repo_t,
+                        batch_size_t,
+                        steps_t,
+                        output_dir_t,
+                        job_name_t,
+                        device_t,
+                        wandb_chk,
+                        policy_repo_t,
+                    ],
+                    train_cmd,
+                )
+
+            # Evaluate Policy Tab
+            with gr.TabItem("Evaluate Policy"):
+                gr.Markdown("### Evaluate Policy")
+                with gr.Row():
+                    robot_type_e = gr.Textbox(label="Robot Type", value="so101_follower")
+                    robot_port_e = gr.Textbox(label="Robot Port", value="/dev/ttyACM0")
+                    robot_id_e = gr.Textbox(label="Robot ID", value="follower")
+                with gr.Row():
+                    cam_index_e = gr.Number(label="Cam Index", value=0, precision=0)
+                    cam_width_e = gr.Number(label="Width", value=640, precision=0)
+                    cam_height_e = gr.Number(label="Height", value=480, precision=0)
+                    cam_fps_e = gr.Number(label="FPS", value=30, precision=0)
+                with gr.Row():
+                    display_data_e = gr.Checkbox(label="Display Data", value=True)
+                    dataset_repo_e = gr.Dropdown(label="User Dataset", choices=_list_remote_datasets(hf_username_tb.value))
+                    num_episodes_e = gr.Number(label="Num Episodes", value=2, precision=0)
+                    single_task_e = gr.Textbox(label="Single Task", value="place cylinder")
+                with gr.Row():
+                    policy_path_e = gr.Textbox(label="Policy Path", value="arpitg1304/smolvla_place_cylinder")
+                    resume_e = gr.Checkbox(label="Resume", value=True)
+                eval_cmd = gr.Textbox(label="Generated Command", interactive=False, lines=16)
+                # update evaluate dataset dropdown when username changes
+                hf_username_tb.change(_update_ds_choices, inputs=hf_username_tb, outputs=dataset_repo_e)
+
+                inputs_eval = [
+                    robot_type_e,
+                    robot_port_e,
+                    robot_id_e,
+                    cam_index_e,
+                    cam_width_e,
+                    cam_height_e,
+                    cam_fps_e,
+                    display_data_e,
+                    dataset_repo_e,
+                    num_episodes_e,
+                    single_task_e,
+                    policy_path_e,
+                    resume_e,
+                ]
+                gr.Button("Generate Command").click(
+                    build_eval_command,
+                    inputs_eval,
+                    eval_cmd,
+                )
+
+    return demo
+
+
+if __name__ == "__main__":
+    build_ui().launch()