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570 lines
83 MiB
570 lines
83 MiB
4 years ago
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 导入相关库"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 53
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},
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"colab_type": "code",
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"id": "wbvMlHd_QwMG",
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"outputId": "669566b2-391f-4596-f290-110e2e177946"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Setup complete. Using torch 1.6.0 CPU\n"
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]
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}
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],
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"source": [
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"import torch\n",
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"import os\n",
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"from IPython.display import Image, clear_output # to display images\n",
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"from utils.google_utils import gdrive_download # to download models/datasets\n",
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"\n",
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"clear_output()\n",
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"print('Setup complete. Using torch %s %s' % (torch.__version__, torch.cuda.get_device_properties(0) if torch.cuda.is_available() else 'CPU'))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"colab_type": "text",
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"id": "N3qM6T0W53gh"
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},
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"source": [
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"## 图像目标检测"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/jpeg": "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"text/plain": [
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"<IPython.core.display.Image object>"
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]
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},
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"execution_count": 2,
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"metadata": {
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"image/jpeg": {
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"width": 600
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}
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},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Image(filename='inference/images/bus.jpg', width=600)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Namespace(agnostic_nms=False, augment=False, classes=None, conf_thres=0.4, device='', img_size=416, iou_thres=0.5, output='inference/output', save_txt=False, source='inference/images/', update=False, view_img=False, weights=['yolov5x.pt'])\n",
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"Using CPU\n",
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"\n",
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"Fusing layers... \n",
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"Model Summary: 284 layers, 8.89222e+07 parameters, 8.45317e+07 gradients\n",
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"image 1/12 /root/yolov5/inference/images/1.jpg: 352x416 4 persons, 2 backpacks, 1 bottles, 10 chairs, 2 tvs, 4 laptops, 2 mouses, 1 keyboards, Done. (0.826s)\n",
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"image 2/12 /root/yolov5/inference/images/2.jpg: 352x416 1 cups, 1 oranges, 1 tvs, 1 laptops, 2 mouses, 1 keyboards, 1 books, Done. (0.775s)\n",
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"image 3/12 /root/yolov5/inference/images/3.jpg: 352x416 4 persons, 1 backpacks, 5 chairs, 1 potted plants, 3 tvs, Done. (0.775s)\n",
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"image 4/12 /root/yolov5/inference/images/4.jpg: 352x416 4 persons, 1 backpacks, 4 chairs, 5 tvs, Done. (0.813s)\n",
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"image 5/12 /root/yolov5/inference/images/5.jpg: 352x416 9 persons, 6 chairs, 7 tvs, 1 keyboards, Done. (0.771s)\n",
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"image 6/12 /root/yolov5/inference/images/7.jpg: 352x416 14 persons, 1 handbags, Done. (0.811s)\n",
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"image 7/12 /root/yolov5/inference/images/9.jpg: 352x416 3 persons, 1 cups, 1 chairs, 6 laptops, Done. (0.773s)\n",
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"image 8/12 /root/yolov5/inference/images/all.jpg: 352x416 14 persons, 1 skateboards, Done. (0.814s)\n",
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"image 9/12 /root/yolov5/inference/images/bus.jpg: 416x352 4 persons, 1 buss, Done. (0.799s)\n",
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"image 10/12 /root/yolov5/inference/images/office1.jpg: 352x416 7 persons, 1 suitcases, 3 chairs, 1 dining tables, Done. (0.813s)\n",
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"image 11/12 /root/yolov5/inference/images/office2.jpg: 352x416 5 persons, 7 chairs, 1 couchs, 1 potted plants, 3 tvs, 1 keyboards, Done. (0.777s)\n",
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"image 12/12 /root/yolov5/inference/images/zidane.jpg: 288x416 3 persons, 1 ties, Done. (0.652s)\n",
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"Results saved to inference/output\n",
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"Done. (13.472s)\n"
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]
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}
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],
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"source": [
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"!python detect.py --weights yolov5x.pt --img 416 --conf 0.4 --source inference/images/"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 图片1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/bus.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"### 图片2"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQoKCgoKBggLDAsKDAkKCgr/2wBDAQICAgICAgUDAwUKBwYHCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgr/wAARCAvQD8ADASIAAhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD8c754WYX9gx+0HkSAbQDsyThRnJ5ApIkt0kdNUiDy3QZfMALORggOEB4YdPep7tY7+eTStQjiVIf3u1JmLBRhmHYE4HTtmq924ayis/s/DTnzIkQCRACrKVx0KglSfeugzH6taW2n3xgmhBtxbhbkMMCOPeW455GRjA6ZA5OKqTwNf2cNzNawQmYFndYhgtlsjHc98YIHXmrT6LEIZbmPzVO1AsssbKRuLHZJuOPlXYScDJIJ65qtfWD6zpqXj3flyRPIyiJcLJ2BXjkjHIxz7cZAJliW1tjDaN5W0D96rkHYerZHp26fritWPVUTTYLy9mIG4mG3aMt57EEAgqON2W/EjjpWHax6kjNbahcwTSAK0KRExIAckblHytkqOBg8HpVqe9uPIiuZVzHFO7SRI5DIXLMCy4yoXPvwB05oAtWl1pFy7kWbtH8sjx3ERMYlJwPlAAHORk9Rx703SItStGngEJPl2xnmQ24YAZ+UIARz046cE1FYXqXNu8U1osTpkCRUwGlZgoKKCCVxjrycD3qzoM8lpeTWcwt5XjmMJiVwPMOBuzkZAG4DvkgigC5ZTiK22RFTG9ws0iADCAqucEcHnHApbOa4uJBD9oKJPdlSQ4BIHRVwNwXOKrQNI9jDFIyllYgn+7kfdA7/AMOKlt9Rt7S6jvg7KFDgRwgNuYqNuUGMMCMkY5oNBkonnv5PtsK/u2ZsoSJ4dvcA9CcLzgZ5wBwKsTyQSStZabZLIEj/ANIZWIWNQQc4xuJO71+7j8KMNpGJZruVlzOjPNE025pAcYG/j+IZ/EVYjhRLQ2hLyQpl1lLBjb5HPHUIBnA7njrQBa01Zr2LdZWCokcTY+Y7GI+8UzznB+v17xYlvJhJALeJDPvn3xoSY2J+TATLcDIbP19Vlie6toLi8tmDRgnzGYYBYLgt1yASORjP15ql9ruLcD/SQd52vcSEsiNjAye3Q8455znbQBba9a0jhW/lWMoQZSoKKwycfLg7sn0HAPJHFOtpWt9Wke4aIlFjOI49pyqhhsVs7V5H1xxjtQd0mltmRo5YYoBG4KbeGPXJxnkdR3/Cr11eXSRpug8tIMGOXqvJAycZY5z07kdOuABuoaNNOXu7qIbcnC7/AC0CD7v0AGAMVJKfO1D+14fMDxr5bh3bYFXoUJB54Ax3bP1MMVreSsDAZp0jXeTCgCkBQ3T+L5iMcHjPvVuLUndIhaW0cRikUGNwGC9OcYBzuPHUHOfoAJp9jdS6lNf3AKE26shcYJ+YcZx8rbRzgEDOaZFJdID9lKozHAUg7lwc4OSdxxnJwcZp05MshcvIZIyPPXzQTtGQx2gknHynpyPxFRJC8Vrc3qXUflsD5ciIDuxgj6Y54OCM8joKAFuba2j8y7hneQYbyLcwCPjGzP4cHPGcVesrSGS7W0mmldxsKbZMMQRy+TyoGMcc/PVCFGuJI0sPOaKQIztC5PlORkqe46ZyehFWvPt7UQ3ivOZBKoaZldiR90oW6cNz6EgVmBJZA3l9KVsEMiv++n244A27FDZ+bJDZB54zmpWvLbTnE1vcefK8uGL8uFHHzE/lngGqkVzNbXgv4LdjLLkFy20F+rZXqpBz6+g6g0uZfsks20W4myh29IzkjkdcE5II6fpQBLfAwKjKqq8jbhCNzOwBBY88N68c8kg9qkkkDsqyxmVHT/R2UfvJ8HJx/sgdMgZIGM1Ua4ieOSe4uNzyPiSVGwYcDG1QDk9SPx5GalhjS3uVgQ+VkjZIy7scbQcHBAzwAeMn0FAF5iZrdNQkkWZ3fCIIyrOeBggcFuQenXOKj0+Py7uSNZRaqNrIxbAlwDkHB6biPqM1Vh8qVWV9jRqh2Op2osmcAfRuCG4qe3v5Ly5ijt2XfcYWO52ApGRnemDyDjHBxmgB8cLpLvutyl5P3LRsMEPlQCv4HB6YFSxSTNid8KWkYx+VgsHCHBzzkEBQelNZjYOWjkYs6fPh96kBjh1GSe2cZ4BqK7uny9tC5j2bAjbQVAB3bge5ycjAAwtZgWZXuTbxySzsJPIfdIzA7iuCcBh97tn0FNbyYZFjjjGBgxI4JI6DaOvGewHaqtk99PK9rK0kitFv53O3A5wR3OMHPrU4Dbd8t0nmbgWjHPA43sw6Nx0BoASQwgvLNMWjRgrAxnJ749O2ePTtUttb2szF2SXcpI2o/lMWCr8oU44IJPqcURQtHi3mjV9w81MIwD7RjGR3/DA685qDF3cs0c1sqFHLSDAJRGH97PIx6D8KALUeiySP54mzGCzQguJAg4wxB9T29vpUduyxSuY7oyHaFETEEMwOFwD94Dk4HJpLvNvYbYN3mbtioSDnIJU+h6A96la4tpohZR2QEm3m2kX/AJagA5wDgDjrn274oAZa6deLqMDTSm32suyLO7ylPAUN0zgEc+o7kCktLu3+0pOERxyrQxMN0ahjnA7jOT2OcYPNRz2UvlCe31LdGyI1uJAd6nH3SBx0B5HXpUr21iIUvDDJOUYnYoLhznADLxxnoeg6c5AoAs6gmnazp7lkEziPEyYOdrDsGwR26/X3PG+KdPi8P7IdOiE0d0DiOUZEMeBwOwAI465xzz06uPUY4tQO8GOPf+9STLqq8ZI4/DH69qmu9FsfEECedAzhLgvbxTOUEXynOcds9MHoexFVGXKB51dJc/ZA2lweaDMpQvGSskvK5C/wgA5yOOKf4Su9QtpYtZ863S5jOA8qgMDuxgqByuCTnNWZvDGq6Vdva3CssUZZIp5CQoBX+E5GVIB6etU5dsAEkcqhkDLCyzMDkZPGQABtbHXtVAdl4c1ODW5H3yPPGJFSfYSgXvgYGGGR7EVuQRTXMFtMJk82TLK5IzgknIJ6+h9O9cBY6rHZWjQzXLKnneYvOxkOQWIZRgE8jtwWxW9pMwEkN5dfeO8KjOcKhBLMAOFIB5J4yTmswOh1KydIhL5du/mSgLMYwSTxnp7hj1PX6USGPT7bzbi9tt7IWgi8gNuY4G4EjjqOe49BzVO2ntVj86+MszmVpP3K/ImR82FYcgFeSe2KtqslyqXE8ZW2fBjaRsE8YDDB+Uc+nvjvQBHthFk8s7oLVI9gKrwXYnBVRwxztGCcfSppnMrL5k6CQhFZgwbOTjKgdTkZ47Zoura0aE2C6bG00jsk8Wz5oyVA3IMZUZ2nIGD0yOhrC3uBNFZm5csFIRgMBcD5TjgD1GPf0oAnEU1y3n3qSxs8mLeK3fLDBIy6nA
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/office2.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"### 图片3"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/zidane.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/1.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/1.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 5,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/7.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 6,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 6,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/7.jpg')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/9.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/9.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/2.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/2.jpg')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/3.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/3.jpg')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/4.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 12,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/4.jpg')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/jpeg": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<IPython.core.display.Image object>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 13,
|
||
|
|
"metadata": {
|
||
|
|
"image/jpeg": {
|
||
|
|
"width": 600
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/images/5.jpg', width=600)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
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"text/plain": [
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"<IPython.core.display.Image object>"
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]
|
||
|
|
},
|
||
|
|
"execution_count": 14,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"Image(filename='inference/output/5.jpg')"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"accelerator": "GPU",
|
||
|
|
"colab": {
|
||
|
|
"collapsed_sections": [],
|
||
|
|
"include_colab_link": true,
|
||
|
|
"name": "YOLOv5 Tutorial",
|
||
|
|
"provenance": [],
|
||
|
|
"toc_visible": true
|
||
|
|
},
|
||
|
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"kernelspec": {
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||
|
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"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
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"language_info": {
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"codemirror_mode": {
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|
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"name": "ipython",
|
||
|
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"version": 3
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||
|
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},
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"file_extension": ".py",
|
||
|
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"mimetype": "text/x-python",
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|
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"name": "python",
|
||
|
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"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
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"version": "3.8.3"
|
||
|
|
}
|
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},
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"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
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