Add support for Stretch (hello-robot) (#409)

Co-authored-by: Remi <remi.cadene@huggingface.co>
Co-authored-by: Remi Cadene <re.cadene@gmail.com>

lerobot/common/robot_devices/cameras/utils.py

@@ -1,55 +1,8 @@
-from pathlib import Path
 from typing import Protocol
 
-import cv2
-import einops
 import numpy as np
 
 
-def write_shape_on_image_inplace(image):
-    height, width = image.shape[:2]
-    text = f"Width: {width} Height: {height}"
-
-    # Define the font, scale, color, and thickness
-    font = cv2.FONT_HERSHEY_SIMPLEX
-    font_scale = 1
-    color = (255, 0, 0)  # Blue in BGR
-    thickness = 2
-
-    position = (10, height - 10)  # 10 pixels from the bottom-left corner
-    cv2.putText(image, text, position, font, font_scale, color, thickness)
-
-
-def save_color_image(image, path, write_shape=False):
-    path = Path(path)
-    path.parent.mkdir(parents=True, exist_ok=True)
-    if write_shape:
-        write_shape_on_image_inplace(image)
-    cv2.imwrite(str(path), image)
-
-
-def save_depth_image(depth, path, write_shape=False):
-    path = Path(path)
-    path.parent.mkdir(parents=True, exist_ok=True)
-
-    # Apply colormap on depth image (image must be converted to 8-bit per pixel first)
-    depth_image = cv2.applyColorMap(cv2.convertScaleAbs(depth, alpha=0.03), cv2.COLORMAP_JET)
-
-    if write_shape:
-        write_shape_on_image_inplace(depth_image)
-    cv2.imwrite(str(path), depth_image)
-
-
-def convert_torch_image_to_cv2(tensor, rgb_to_bgr=True):
-    assert tensor.ndim == 3
-    c, h, w = tensor.shape
-    assert c < h and c < w
-    color_image = einops.rearrange(tensor, "c h w -> h w c").numpy()
-    if rgb_to_bgr:
-        color_image = cv2.cvtColor(color_image, cv2.COLOR_RGB2BGR)
-    return color_image
-
-
 # Defines a camera type
 class Camera(Protocol):
     def connect(self): ...