insaneyilin

#!/usr/bin/env python3
"""
Object detection using Ollama vision models.

Usage: python ollama_object_detect.py <input_image_file_path> <object_text> <output_dir>

Arguments:
- input_image_file_path: Path to the input image file
- object_text: Object category description to detect (e.g., "dog", "cat")
- output_dir: Output directory where detection results will be saved

insaneyilin

def get_last_valid_indices(valid_mask):
    """Get the last valid indices for each sample.

    Args:
        valid_mask (torch.Tensor): [B, seq_len], True if valid

    Returns:
        torch.Tensor: [B,], Last valid indices for each sample.
    """
    # 反转mask

insaneyilin

import argparse

from PIL import Image

def embed_message(image_path, message, output_path):
    org_img = Image.open(image_path)
    org_pixelMap = org_img.load()

    enc_img = Image.new(org_img.mode, org_img.size)
    enc_pixelsMap = enc_img.load()

insaneyilin

#!/bin/bash

# Check number of arguments
if [ $# -ne 3 ]; then
    echo "Usage: $0 <file1> <file2> <output_file>"
    echo "Example: $0 file1.txt file2.txt differences.txt"
    exit 1
fi

# Get command line arguments

insaneyilin

ffmpeg -ss 0 -t 3 -i input.mp4 \
    -vf "fps=10,scale=320:-1:flags=lanczos,split[s0][s1];[s0]palettegen[p];[s1][p]paletteuse" \
    -loop 0 output.gif

insaneyilin

# 保存到 ~/.gdbinit
python
import sys 
sys.path.insert(0, '/usr/share/gcc-4.8.2/python') # 这个路径以实际情况为准
from libstdcxx.v6.printers import register_libstdcxx_printers
register_libstdcxx_printers (None)
end

#                                                                                                        
#   STL GDB evaluators/views/utilities - 1.03

insaneyilin

def tile_along_axis(x, dim, n_tile):
    init_dim = x.size(dim)
    repeat_idx = [1] * x.dim()
    repeat_idx[dim] = n_tile
    x = x.repeat(*(repeat_idx))
    order_index = torch.tensor(
        torch.cat([init_dim * torch.arange(n_tile, device=x.device) + i for i in range(init_dim)]),
        dtype=torch.long, device=x.device)
    return torch.index_select(x, dim, order_index)

insaneyilin

#!/bin/bash
while true
do
    x=`xdotool getmouselocation | grep -oP '(?<=x:)\d+'`
    y=`xdotool getmouselocation | grep -oP '(?<=y:)\d+'`
    xdotool mousemove $x $y
    xdotool click 1
    sleep 1
done

insaneyilin

vector <string> Names {"Karl", "Martin", "Paul", "Jennie"};
vector <int> Score{45, 5, 14, 24};

std::vector<int> indices(Names.size());
 std::iota(indices.begin(), indices.end(), 0);
 std::sort(indices.begin(), indices.end(),
           [&](int A, int B) -> bool {
                return Score[A] < Score[B];
            });

insaneyilin

import numpy as np
from scipy.spatial import KDTree


def chamfer_distance(s1, s2, direction='s2_to_s1'):
    """Chamfer distance between two point sets.

    Args:
        s1 (np.ndarray): [n_points_s1, n_dims]
        s2 (np.ndarray): [n_points_s2, n_dims]