我需要一个利用pytorch库编写的全景图像拼接代码

好的，我可以为您提供使用pytorch库编写的全景图像拼接代码。以下是代码实现：

import torch
import torch.nn as nn
import numpy as np
from PIL import Image

class PanoramaStitcher(nn.Module):
    def __init__(self):
        super(PanoramaStitcher, self).__init__()

    def forward(self, images, focal_lengths=None):
        """
        images: a list of PIL images representing the images to stitch together
        focal_lengths: a list of focal lengths for corresponding images, defaults to [500.0] * len(images)

        return: a PIL image with the stitched panorama
        """
        w, h = images[0].size
        device = images[0].convert("RGB").getpixel((0, 0))  # will help us determine device later

        if focal_lengths is None:
            focal_lengths = [500.0] * len(images)

        panoramas = []
        for image, f in zip(images, focal_lengths):
            tw = f * np.arctan(w / (2 * f)) * 2  # total width of image at this focal length
            K = torch.tensor([[f, 0, w / 2], [0, f, h / 2], [0, 0, 1]])

            # calculate the projection matrix P
            rot_angle = np.deg2rad(np.random.randint(-10, 10))
            rot_matrix = torch.tensor(
                [
                    [1, 0, 0],
                    [0, np.cos(rot_angle), -np.sin(rot_angle)],
                    [0, np.sin(rot_angle), np.cos(rot_angle)],
                ]
            )
            T = torch.tensor([[1, 0, np.random.randint(-5, 5)], [0, 1, np.random.randint(-5, 5)], [0, 0, 1]])
            P = K @ (rot_matrix @ T)

            # warp the image with P
            image_tensor = torch.tensor(np.array(image)).permute(2, 0, 1).unsqueeze(0)  # CHW format
            grid = torch.nn.functional.affine_grid(P[:2, :].unsqueeze(0), image_tensor.shape)
            warped_image = torch.nn.functional.grid_sample(image_tensor.float(), grid).squeeze()

            # increase the width of the canvas
            new_w = int(torch.round(torch.tensor(w * f / focal_lengths[0])))
            canvas = np.zeros((h, new_w, 3), dtype=np.uint8) + device
            canvas[:, :w] = np.array(image)

            # blend the warped image with canvas
            mask = (warped_image > 0).float()
            overlap = (canvas != device).float()
            blend_mask = torch.min(mask + overlap, torch.tensor(1.0))

            canvas[:h, -new_w + w:] += (warped_image * blend_mask).permute(1, 2, 0).numpy().astype(np.uint8)

            panoramas.append(canvas)

        concatenated_panorama = np.concatenate(panoramas, axis=1)

        return Image.fromarray(concatenated_panorama)

# Example usage:
images = [Image.open(f"image_{i}.jpg").convert("RGB") for i in range(1, 4)]
panorama_stitcher = PanoramaStitcher()
stitched_panorama = panorama_stitcher(images)
stitched_panorama.save("stitched_panorama.png")

这是一个简单的全景图像拼接代码，使用了pytorch库和PIL库进行图像处理和数学计算。您可以将其保存为.py文件并在命令行或其他脚本中调用。希望对您有所帮助。