# **LINE_Notify研究版本集(~8/26)**
###### tags: `藍柏婷`
###### tags: `2021/08/26`
## **## 所有程式碼集(依時間排序)**
### **== LINE_Notify_0 ==**
```python=
import requests
def SendMessageToLineNotify(message, pic):
Token = "WWjgIOXkPZq7RrRGwIUnru3ivMPwqc1g3EMT1Ryo7lx" # 你的權杖
url = "https://notify-api.line.me/api/notify" # 跑不出來的某網站
# my_files = {'my_filename': open('C:/Users/藍柏婷/Desktop/竹女網自我介紹詞.docx', 'rb')}
payload = {'message':message,
# 文字
'imageThumbnail':pic,
'imageFullsize':pic,
# 圖片
# imageThumbnail、imageFullsize為成對的圖片，各有尺寸大小
'stickerPackageId':446,
'stickerId':1988
# 貼圖
# stickerPackageId、stickerId為貼圖成對的編號
# 可參見Line Sticker List總表 https://developers.line.biz/en/docs/messaging-api/sticker-list/#sticker-definitions
} # 要傳送的訊息
header = {'Content-Type':'application/x-www-form-urlencoded',
# 在 HTTP 中有兩種 POST 數據的方式：application/x-www-form-urlencoded和multipart/form-data。
# 如果您要傳輸二進制（非字母數字）數據（或非常大的有效負載），請使用multipart/form-data。
# 否則，請使用application/x-www-form-urlencoded。
'Authorization':'Bearer ' + Token # 根據使用者的角色來授予應有的權限 # 不要手殘把'Bearer '中的空格弄掉!!!會出事!!!
} # 自訂請求表投
r=requests.post(url, headers=header, data=payload) # 將文字、照片、貼圖傳送出去
print(r.text) # 回傳" {"status":200,"message":"ok"} "的指示(.text可以查看資料)
def main():
message = '小雞好可愛' # 提示文字
pic = 'https://imgcdn.cna.com.tw/www/WebPhotos/800/20210427/1920x1280_581754849593.jpg' # 圖片
SendMessageToLineNotify(message, pic)
if __name__ == '__main__': # 可避免電腦將引用之程式的主程式也一併執行
main()
```
### **== LINE_Notify_1 ==**
```python=
import requests
send={ # 網路上大多叫"payload"
'message':"火災警示",
'imageThumbnail':'https://imgcdn.cna.com.tw/www/WebPhotos/800/20210427/1920x1280_581754849593.jpg',
'imageFullsize':'https://imgcdn.cna.com.tw/www/WebPhotos/800/20210427/1920x1280_581754849593.jpg',
}
header={
'Content-Type':'application/x-www-form-urlencoded',
'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"
}
r=requests.post("https://notify-api.line.me/api/notify", headers=header, data=send)
print(r.text)
```
### **== LINE_Notify_2 ==**
```python=
import requests
# from my-recognition import class_idx
def send_to_line(category='',pic=''):
send={
'message':("嗨陌生人你用到我們的pincode了 所以傳不到你那邊啦"),
'imageThumbnail':pic,
'imageFullsize':pic,
}
header={
'Content-Type':'application/x-www-form-urlencoded',
'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"
}
r=requests.post("https://notify-api.line.me/api/notify", headers=header, data=send)
print(r.text) # {"status":200,"message":"ok"}
danger=False
if danger!=True:
category="microwave"
pic='https://memeprod.sgp1.digitaloceanspaces.com/user-wtf/1622455521876.jpg'
send_to_line(category,pic)
```
### **== LINE_Notify_3 ==**
```python=
import jetson.inference
import jetson.utils
import requests
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
#camera = jetson.utils.videoSource("csi://0") # csi camera
camera = jetson.utils.videoSource("/dev/video0") # usb camera
display = jetson.utils.videoOutput("display://0") # 'my_video.mp4' for file
def send_to_line(category='',pic=''):
send={
'message':("嗨陌生人你用到我們的pincode了 所以傳不到你那邊啦"),
'imageThumbnail':pic,
'imageFullsize':pic,
}
header={
'Content-Type':'application/x-www-form-urlencoded',
'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"
}
r=requests.post("https://notify-api.line.me/api/notify", headers=header, data=send)
print(r.text) # {"status":200,"message":"ok"}
while True:
img = camera.Capture()
detections = net.Detect(img)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
danger=False
if danger!=True:
category="microwave"
pic='https://memeprod.sgp1.digitaloceanspaces.com/user-wtf/1622455521876.jpg'
send_to_line(category,pic)
if not camera.IsStreaming() or not display.IsStreaming():
break
```
### **== LINE_Notify_4 ==**
```python=
import cv2
import requests
def send_to_line(category,pic):
params = {'message':"\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)}
files = {'imageFile': open(pic, 'rb')}
headers = {'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"}
r = requests.post("https://notify-api.line.me/api/notify", headers=headers, params=params, files=files)
print(r.text)
cap = cv2.VideoCapture(1)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920) # 畫面寬度設定為 1920
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080) # 畫面高度設定為 1080
cv2.namedWindow('image_win',flags=cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_EXPANDED)
img_count = 1
while(True):
ret, frame = cap.read()
cv2.imshow('image_win',frame) # 更新窗口“image_win”中的圖片 # 不可以刪掉，否則會沒有畫面
key = cv2.waitKey(1) # 等待按鍵事件發生 等待1ms
if key == ord('q'):
break
elif key == ord('c'): # 如果c键按下，則進行圖片保存
cv2.imwrite("{}.png".format(img_count), frame) # 寫入圖片 并命名圖片為 <img_count>.png
category = "microwave"
pic = 'C:/Users/藍柏婷/Desktop/Python/{}.png'.format(img_count)
send_to_line(category,pic)
img_count += 1
cap.release() # 釋放VideoCapture
cv2.destroyAllWindows() # 銷毀所有的窗口
```
### **== my-detection_2.py ==**
```python=
import jetson.inference
import jetson.utils
import requests
import cv2
def send_to_line(category='',pic=''):
send={
'message':("\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)),
'imageThumbnail':pic,
'imageFullsize':pic,
}
header={
'Content-Type':'application/x-www-form-urlencoded',
'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"
}
r=requests.post("https://notify-api.line.me/api/notify", headers=header, data=send)
print(r.text) # {"status":200,"message":"ok"}
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0") # usb camera
display = jetson.utils.videoOutput("display://0") # 'my_video.mp4' for file
i=0
while True:
img = camera.Capture()
detections = net.Detect(img)
if len(detections)>=1:
ret,frame=camera.read()
cv2.imshow("frame",frame)
category="book"
pic='https://imgcdn.cna.com.tw/www/WebPhotos/800/20210427/1920x1280_581754849593.jpg'
send_to_line(category,pic)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if not camera.IsStreaming() or not display.IsStreaming():
break
```
### **== my-detection_3.py ==**
```python=
import jetson.inference
import jetson.utils
import requests
def send_to_line(category='',pic=''):
send={
'message':("\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)),
'imageThumbnail':pic,
'imageFullsize':pic,
}
header={
'Content-Type':'application/x-www-form-urlencoded',
'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"
}
r=requests.post("https://notify-api.line.me/api/notify", headers=header, data=send)
print(r.text) # {"status":200,"message":"ok"}
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0") # usb camera
display = jetson.utils.videoOutput("display://0") # 'my_video.mp4' for file
while True:
img = camera.Capture()
detections = net.Detect(img)
if len(detections)>=1:
category="book"
pic='https://imgcdn.cna.com.tw/www/WebPhotos/800/20210427/1920x1280_581754849593.jpg'
send_to_line(category,pic)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if not camera.IsStreaming() or not display.IsStreaming():
break
```
### **== LINE_Notify_5 ==**
```python=
import jetson.inference
import jetson.utils
import requests
import cv2
def send_to_line(category,pic):
params = {'message':"\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)}
files = {'imageFile': open(pic, 'rb')}
headers = {'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"}
r = requests.post("https://notify-api.line.me/api/notify", headers=headers, params=params, files=files)
print(r.text)
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0") # usb camera
display = jetson.utils.videoOutput("display://0") # 'my_video.mp4' for file
# camera.set(cv2.CAP_PROP_FRAME_WIDTH, 1920) # 畫面寬度設定為 1920
# camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080) # 畫面高度設定為 1080
# cv2.namedWindow('image_win',flags=cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_EXPANDED)
while True:
img = camera.Capture()
detections = net.Detect(img)
if len(detections)>=1:
img_count = 1
# frame = camera.read()
cv2.imshow('image_win',img) # 更新窗口“image_win”中的圖片 # 不可以刪掉，否則會沒有畫面
key = cv2.waitKey(1) # 等待按鍵事件發生 等待1ms
if key == ord('q'):
break
elif key == ord('c'): # 如果c键按下，則進行圖片保存
cv2.imwrite("{}.png".format(img_count), img) # 寫入圖片 并命名圖片為 <img_count>.png
category = "microwave"
pic = '/home/iamai2021/Desktop/{}.png'.format(img_count)
send_to_line(category,pic)
img_count += 1
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if not camera.IsStreaming() or not display.IsStreaming():
break
# cap.release() # 釋放VideoCapture
# cv2.destroyAllWindows() # 銷毀所有的窗口
```
### **== LINE_Notify_6 ==**
```python=
import jetson.inference
import jetson.utils
import requests
import cv2
def send_to_line(category,pic):
params = {'message':"\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)}
files = {'imageFile': open(pic, 'rb')}
headers = {'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"}
r = requests.post("https://notify-api.line.me/api/notify", headers=headers, params=params, files=files)
print(r.text)
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0") # usb camera
display = jetson.utils.videoOutput("display://0") # 'my_video.mp4' for file
# camera.set(cv2.CAP_PROP_FRAME_WIDTH, 1920) # 畫面寬度設定為 1920
# camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080) # 畫面高度設定為 1080
# cv2.namedWindow('image_win',flags=cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_EXPANDED)
img_count = 1
while True:
img = camera.Capture()
detections = net.Detect(img)
# frame=display.Render(img)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if len(detections)>=1:
cv2.imwrite("{}.png".format(img_count), frame) # 寫入圖片 并命名圖片為 <img_count>.png
# frame = camera.read()
# cv2.imshow('image_win',frame) # 更新窗口“image_win”中的圖片 # 不可以刪掉，否則會沒有畫面
# key = cv2.waitKey(1) # 等待按鍵事件發生 等待1ms
# if key == ord('q'):
# break
# elif key == ord('c'): # 如果c键按下，則進行圖片保存
# cv2.imwrite("{}.png".format(img_count), frame) # 寫入圖片 并命名圖片為 <img_count>.png
category = "microwave"
pic = '/home/iamai2021/Desktop/{}.png'.format(img_count)
send_to_line(category,pic)
img_count += 1
if not camera.IsStreaming() or not display.IsStreaming():
break
```
### **== LINE_Notify_7 ==**
```python=
import jetson.inference
import jetson.utils
import requests
def send_to_line(category,pic):
params = {'message':"\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)}
files = {'imageFile': open(pic, 'rb')}
headers = {'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"}
r = requests.post("https://notify-api.line.me/api/notify", headers=headers, params=params, files=files)
print(r.text)
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0")
display = jetson.utils.videoOutput("file://my_image.jpg")
while True:
img = camera.Capture()
detections = net.Detect(img)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if len(detections)>=1:
category = "microwave"
pic = '/home/iamai2021/Desktop/my_image.jpg'
send_to_line(category,pic)
if not camera.IsStreaming() or not display.IsStreaming():
break
```
## **## 最終版展示**
### **== LINE_Notify_7 ==**
```python=
import jetson.inference
import jetson.utils
import requests
def send_to_line(category,pic):
params = {'message':"\n嗨，你好\n這是 \"火災警示\" 通知\n請注意!!\n偵測到 \"{0}\" 溫度過高".format(category)}
files = {'imageFile': open(pic, 'rb')}
headers = {'Authorization':'Bearer ' + "gOljwt8lLAnbpWSIXUk3RJP34Syw6NQADBtorl2GoCP"}
r = requests.post("https://notify-api.line.me/api/notify", headers=headers, params=params, files=files)
print(r.text)
net = jetson.inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
camera = jetson.utils.videoSource("/dev/video0")
display = jetson.utils.videoOutput("file://my_image.jpg")
while True:
img = camera.Capture()
detections = net.Detect(img)
display.Render(img)
display.SetStatus("Object Detection | Network {:.0f} FPS".format(net.GetNetworkFPS()))
if len(detections)>=1:
category = "microwave"
pic = '/home/iamai2021/Desktop/my_image.jpg'
send_to_line(category,pic)
if not camera.IsStreaming() or not display.IsStreaming():
break
```
### **== 跑出結果 ==**
:::success
**#跑出結果**
```python
iamai2021@iamai2021:~/Desktop$ python3 LINE_Notify_5.py
/usr/lib/python3/dist-packages/requests/__init__.py:80: RequestsDependencyWarning: urllib3 (1.26.6) or chardet (3.0.4) doesn't match a supported version!
RequestsDependencyWarning)
jetson.inference -- detectNet loading build-in network 'ssd-mobilenet-v2'
detectNet -- loading detection network model from:
-- model networks/SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff
-- input_blob 'Input'
-- output_blob 'NMS'
-- output_count 'NMS_1'
-- class_labels networks/SSD-Mobilenet-v2/ssd_coco_labels.txt
-- threshold 0.500000
-- batch_size 1
[TRT] TensorRT version 7.1.3
[TRT] loading NVIDIA plugins...
[TRT] Registered plugin creator - ::GridAnchor_TRT version 1
[TRT] Registered plugin creator - ::NMS_TRT version 1
[TRT] Registered plugin creator - ::Reorg_TRT version 1
[TRT] Registered plugin creator - ::Region_TRT version 1
[TRT] Registered plugin creator - ::Clip_TRT version 1
[TRT] Registered plugin creator - ::LReLU_TRT version 1
[TRT] Registered plugin creator - ::PriorBox_TRT version 1
[TRT] Registered plugin creator - ::Normalize_TRT version 1
[TRT] Registered plugin creator - ::RPROI_TRT version 1
[TRT] Registered plugin creator - ::BatchedNMS_TRT version 1
[TRT] Could not register plugin creator - ::FlattenConcat_TRT version 1
[TRT] Registered plugin creator - ::CropAndResize version 1
[TRT] Registered plugin creator - ::DetectionLayer_TRT version 1
[TRT] Registered plugin creator - ::Proposal version 1
[TRT] Registered plugin creator - ::ProposalLayer_TRT version 1
[TRT] Registered plugin creator - ::PyramidROIAlign_TRT version 1
[TRT] Registered plugin creator - ::ResizeNearest_TRT version 1
[TRT] Registered plugin creator - ::Split version 1
[TRT] Registered plugin creator - ::SpecialSlice_TRT version 1
[TRT] Registered plugin creator - ::InstanceNormalization_TRT version 1
[TRT] detected model format - UFF (extension '.uff')
[TRT] desired precision specified for GPU: FASTEST
[TRT] requested fasted precision for device GPU without providing valid calibrator, disabling INT8
[TRT] native precisions detected for GPU: FP32, FP16
[TRT] selecting fastest native precision for GPU: FP16
[TRT] attempting to open engine cache file /usr/local/bin/networks/SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff.1.1.7103.GPU.FP16.engine
[TRT] loading network plan from engine cache... /usr/local/bin/networks/SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff.1.1.7103.GPU.FP16.engine
[TRT] device GPU, loaded /usr/local/bin/networks/SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff
[TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
[TRT] Deserialize required 7629430 microseconds.
[TRT]
[TRT] CUDA engine context initialized on device GPU:
[TRT] -- layers 119
[TRT] -- maxBatchSize 1
[TRT] -- workspace 0
[TRT] -- deviceMemory 35486720
[TRT] -- bindings 3
[TRT] binding 0
-- index 0
-- name 'Input'
-- type FP32
-- in/out INPUT
-- # dims 3
-- dim #0 3 (SPATIAL)
-- dim #1 300 (SPATIAL)
-- dim #2 300 (SPATIAL)
[TRT] binding 1
-- index 1
-- name 'NMS'
-- type FP32
-- in/out OUTPUT
-- # dims 3
-- dim #0 1 (SPATIAL)
-- dim #1 100 (SPATIAL)
-- dim #2 7 (SPATIAL)
[TRT] binding 2
-- index 2
-- name 'NMS_1'
-- type FP32
-- in/out OUTPUT
-- # dims 3
-- dim #0 1 (SPATIAL)
-- dim #1 1 (SPATIAL)
-- dim #2 1 (SPATIAL)
[TRT]
[TRT] binding to input 0 Input binding index: 0
[TRT] binding to input 0 Input dims (b=1 c=3 h=300 w=300) size=1080000
[TRT] binding to output 0 NMS binding index: 1
[TRT] binding to output 0 NMS dims (b=1 c=1 h=100 w=7) size=2800
[TRT] binding to output 1 NMS_1 binding index: 2
[TRT] binding to output 1 NMS_1 dims (b=1 c=1 h=1 w=1) size=4
[TRT]
[TRT] device GPU, /usr/local/bin/networks/SSD-Mobilenet-v2/ssd_mobilenet_v2_coco.uff initialized.
[TRT] W = 7 H = 100 C = 1
[TRT] detectNet -- maximum bounding boxes: 100
[TRT] detectNet -- loaded 91 class info entries
[TRT] detectNet -- number of object classes: 91
[gstreamer] initialized gstreamer, version 1.14.5.0
[gstreamer] gstCamera -- attempting to create device v4l2:///dev/video0
[gstreamer] gstCamera -- found v4l2 device: UVC Camera (046d:0825)
[gstreamer] v4l2-proplist, device.path=(string)/dev/video0, udev-probed=(boolean)false, device.api=(string)v4l2, v4l2.device.driver=(string)uvcvideo, v4l2.device.card=(string)"UVC\ Camera\ \(046d:0825\)", v4l2.device.bus_info=(string)usb-70090000.xusb-2, v4l2.device.version=(uint)264649, v4l2.device.capabilities=(uint)2216689665, v4l2.device.device_caps=(uint)69206017;
[gstreamer] gstCamera -- found 38 caps for v4l2 device /dev/video0
[gstreamer] [0] video/x-raw, format=(string)YUY2, width=(int)1280, height=(int)960, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 15/2, 5/1 };
[gstreamer] [1] video/x-raw, format=(string)YUY2, width=(int)1280, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 15/2, 5/1 };
[gstreamer] [2] video/x-raw, format=(string)YUY2, width=(int)1184, height=(int)656, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 10/1, 5/1 };
[gstreamer] [3] video/x-raw, format=(string)YUY2, width=(int)960, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 10/1, 5/1 };
[gstreamer] [4] video/x-raw, format=(string)YUY2, width=(int)1024, height=(int)576, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 10/1, 5/1 };
[gstreamer] [5] video/x-raw, format=(string)YUY2, width=(int)960, height=(int)544, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 15/1, 10/1, 5/1 };
[gstreamer] [6] video/x-raw, format=(string)YUY2, width=(int)800, height=(int)600, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [7] video/x-raw, format=(string)YUY2, width=(int)864, height=(int)480, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [8] video/x-raw, format=(string)YUY2, width=(int)800, height=(int)448, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [9] video/x-raw, format=(string)YUY2, width=(int)752, height=(int)416, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [10] video/x-raw, format=(string)YUY2, width=(int)640, height=(int)480, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [11] video/x-raw, format=(string)YUY2, width=(int)640, height=(int)360, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [12] video/x-raw, format=(string)YUY2, width=(int)544, height=(int)288, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [13] video/x-raw, format=(string)YUY2, width=(int)432, height=(int)240, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [14] video/x-raw, format=(string)YUY2, width=(int)352, height=(int)288, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [15] video/x-raw, format=(string)YUY2, width=(int)320, height=(int)240, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [16] video/x-raw, format=(string)YUY2, width=(int)320, height=(int)176, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [17] video/x-raw, format=(string)YUY2, width=(int)176, height=(int)144, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [18] video/x-raw, format=(string)YUY2, width=(int)160, height=(int)120, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [19] image/jpeg, width=(int)1280, height=(int)960, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [20] image/jpeg, width=(int)1280, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [21] image/jpeg, width=(int)1184, height=(int)656, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [22] image/jpeg, width=(int)960, height=(int)720, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [23] image/jpeg, width=(int)1024, height=(int)576, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [24] image/jpeg, width=(int)960, height=(int)544, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [25] image/jpeg, width=(int)800, height=(int)600, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [26] image/jpeg, width=(int)864, height=(int)480, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [27] image/jpeg, width=(int)800, height=(int)448, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [28] image/jpeg, width=(int)752, height=(int)416, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [29] image/jpeg, width=(int)640, height=(int)480, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [30] image/jpeg, width=(int)640, height=(int)360, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [31] image/jpeg, width=(int)544, height=(int)288, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [32] image/jpeg, width=(int)432, height=(int)240, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [33] image/jpeg, width=(int)352, height=(int)288, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [34] image/jpeg, width=(int)320, height=(int)240, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [35] image/jpeg, width=(int)320, height=(int)176, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [36] image/jpeg, width=(int)176, height=(int)144, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] [37] image/jpeg, width=(int)160, height=(int)120, pixel-aspect-ratio=(fraction)1/1, framerate=(fraction){ 30/1, 25/1, 20/1, 15/1, 10/1, 5/1 };
[gstreamer] gstCamera -- selected device profile: codec=mjpeg format=unknown width=1280 height=720
[gstreamer] gstCamera pipeline string:
[gstreamer] v4l2src device=/dev/video0 ! image/jpeg, width=(int)1280, height=(int)720 ! jpegdec ! video/x-raw ! appsink name=mysink
[gstreamer] gstCamera successfully created device v4l2:///dev/video0
[video] created gstCamera from v4l2:///dev/video0
------------------------------------------------
gstCamera video options:
------------------------------------------------
-- URI: v4l2:///dev/video0
- protocol: v4l2
- location: /dev/video0
-- deviceType: v4l2
-- ioType: input
-- codec: mjpeg
-- width: 1280
-- height: 720
-- frameRate: 30.000000
-- bitRate: 0
-- numBuffers: 4
-- zeroCopy: true
-- flipMethod: none
-- loop: 0
-- rtspLatency 2000
------------------------------------------------
[video] created imageWriter from file://my_image.jpg
------------------------------------------------
imageWriter video options:
------------------------------------------------
-- URI: file://my_image.jpg
- protocol: file
- location: my_image.jpg
- extension: jpg
-- deviceType: file
-- ioType: output
-- codec: unknown
-- width: 0
-- height: 0
-- frameRate: 0.000000
-- bitRate: 0
-- numBuffers: 4
-- zeroCopy: true
-- flipMethod: none
-- loop: 0
-- rtspLatency 2000
------------------------------------------------
[OpenGL] glDisplay -- X screen 0 resolution: 1920x1080
[OpenGL] glDisplay -- X window resolution: 1920x1080
[OpenGL] glDisplay -- display device initialized (1920x1080)
[video] created glDisplay from display://0
------------------------------------------------
glDisplay video options:
------------------------------------------------
-- URI: display://0
- protocol: display
- location: 0
-- deviceType: display
-- ioType: output
-- codec: raw
-- width: 1920
-- height: 1080
-- frameRate: 0.000000
-- bitRate: 0
-- numBuffers: 4
-- zeroCopy: true
-- flipMethod: none
-- loop: 0
-- rtspLatency 2000
------------------------------------------------
[gstreamer] opening gstCamera for streaming, transitioning pipeline to GST_STATE_PLAYING
[gstreamer] gstreamer changed state from NULL to READY ==> mysink
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter1
[gstreamer] gstreamer changed state from NULL to READY ==> jpegdec0
[gstreamer] gstreamer changed state from NULL to READY ==> capsfilter0
[gstreamer] gstreamer changed state from NULL to READY ==> v4l2src0
[gstreamer] gstreamer changed state from NULL to READY ==> pipeline0
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter1
[gstreamer] gstreamer changed state from READY to PAUSED ==> jpegdec0
[gstreamer] gstreamer changed state from READY to PAUSED ==> capsfilter0
[gstreamer] gstreamer stream status CREATE ==> src
[gstreamer] gstreamer changed state from READY to PAUSED ==> v4l2src0
[gstreamer] gstreamer changed state from READY to PAUSED ==> pipeline0
[gstreamer] gstreamer stream status ENTER ==> src
[gstreamer] gstreamer message new-clock ==> pipeline0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter1
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> jpegdec0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> capsfilter0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> v4l2src0
[gstreamer] gstreamer message stream-start ==> pipeline0
[gstreamer] gstCamera -- onPreroll
[gstreamer] gstCamera -- map buffer size was less than max size (1382400 vs 1382407)
[gstreamer] gstCamera recieve caps: video/x-raw, format=(string)I420, width=(int)1280, height=(int)720, interlace-mode=(string)progressive, multiview-mode=(string)mono, multiview-flags=(GstVideoMultiviewFlagsSet)0:ffffffff:/right-view-first/left-flipped/left-flopped/right-flipped/right-flopped/half-aspect/mixed-mono, pixel-aspect-ratio=(fraction)1/1, chroma-site=(string)mpeg2, colorimetry=(string)1:4:0:0, framerate=(fraction)30/1
[gstreamer] gstCamera -- recieved first frame, codec=mjpeg format=i420 width=1280 height=720 size=1382407
RingBuffer -- allocated 4 buffers (1382407 bytes each, 5529628 bytes total)
[gstreamer] gstreamer changed state from READY to PAUSED ==> mysink
[gstreamer] gstreamer message async-done ==> pipeline0
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> mysink
[gstreamer] gstreamer changed state from PAUSED to PLAYING ==> pipeline0
RingBuffer -- allocated 4 buffers (2764800 bytes each, 11059200 bytes total)
[OpenGL] glDisplay -- set the window size to 1280x720
[OpenGL] creating 1280x720 texture (GL_RGB8 format, 2764800 bytes)
[cuda] registered openGL texture for interop access (1280x720, GL_RGB8, 2764800 bytes)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[gstreamer] gstreamer message qos ==> v4l2src0
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
{"status":200,"message":"ok"}
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
{"status":200,"message":"ok"}
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
{"status":200,"message":"ok"}
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
{"status":200,"message":"ok"}
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[OpenGL] glDisplay -- the window has been closed
[image] saved 'my_image.jpg' (1280x720, 3 channels)
[gstreamer] gstCamera -- stopping pipeline, transitioning to GST_STATE_NULL
[gstreamer] gstCamera -- onPreroll
[gstreamer] gstCamera -- pipeline stopped
```
:::
### **== 實際效果 ==**
:::success
**#實際效果**
:::
## **## 結論**
:::info
**LINE Notify圖片及文字傳輸 DONE!**
:::
## **## 所有參考網站**
### **LINE_Notify**
* https://engineering.linecorp.com/zh-hant/blog/using-line-notify-to-send-stickers-and-upload-images/
* https://blog.miniasp.com/post/2020/02/17/Go-Through-LINE-Notify-Without-Any-Code
* https://www.oxxostudio.tw/articles/201806/line-notify.html
* http://white5168.blogspot.com/2017/01/line-notify-4-line-notify.html
* https://vimsky.com/zh-tw/examples/usage/python-pil-image-thumbnail-method.html
* https://ithelp.ithome.com.tw/articles/10234576
* https://notify-bot.line.me/doc/en/
* https://eason851021.medium.com/line-notify-%E5%88%A9%E7%94%A8python%E5%82%B3%E9%80%81%E5%AE%A2%E8%A3%BD%E5%8C%96%E8%A8%8A%E6%81%AF-%E4%BB%A5%E5%90%89%E5%A8%83%E5%A8%83%E9%95%B7%E8%BC%A9%E5%9C%96%E7%82%BA%E4%BE%8B-2a50c6a5197b
* http://blog.3dgowl.com/arduino-esp32%E4%B8%89-%E4%BD%BF%E7%94%A8-esp32-cam-%E6%8B%8D%E7%85%A7%E4%B8%A6%E5%82%B3line%E9%80%9A%E7%9F%A5/
* http://cheng-min-i-taiwan.blogspot.com/2018/02/line-bot-notify-aspnet-vbnet.html
* https://www.rs-online.com/designspark/nvidia-jetson-nano-line-cn
* https://www.learncodewithmike.com/2020/06/python-line-notify.html
* https://ithelp.ithome.com.tw/questions/10201732
### **LINE_Robot**
* https://engineering.linecorp.com/zh-hant/blog/line-device-10/
### **Requests**
* https://docs.python-requests.org/en/master/
* https://blog.gtwang.org/programming/python-requests-module-tutorial/
### **Bearer Token**
* https://blog.yorkxin.org/posts/oauth2-6-bearer-token.html
* https://ithelp.ithome.com.tw/articles/10197166
### **Keras**
* https://keras.io/guides/functional_api/
* https://ithelp.ithome.com.tw/articles/10191627
* https://vimsky.com/zh-tw/examples/detail/python-method-keras.models.load_model.html
* https://github.com/tensorflow/tensorflow/issues/26813
* https://github.com/googlecreativelab/teachablemachine-community/blob/master/snippets/markdown/image/tensorflow/keras.md
* https://hoohoo.top/blog/several-ways-to-solve-the-no-module-named-kerasmodels-error/
### **Webhook**
* https://jp.cybozu.help/k/zh-tw/user/app_settings/set_webhook/webhook.html
### **Tensorflow**
* https://blog.csdn.net/blueheart20/article/details/78980736
* https://forums.developer.nvidia.com/t/official-tensorflow-for-jetson-nano/71770
* https://www.daimajiaoliu.com/daima/47991c649100407
### **shell**
* https://blog.csdn.net/weixin_37913042/article/details/103968504
* https://www.runoob.com/linux/linux-shell.html
* https://zhuanlan.zhihu.com/p/104729643
### **Parser/Argparse**
* http://inspiregate.com/programming/other/476-compiler-3-3.html
* https://docs.python.org/zh-tw/3/howto/argparse.html
### **WebDriver API**
* https://selenium-python.readthedocs.io/api.html
### **OpenCV**
* http://www.1zlab.com/wiki/python-opencv-tutorial/opencv-read-usb-camera-image/
* https://blog.gtwang.org/programming/opencv-webcam-video-capture-and-file-write-tutorial/
* https://blog.gtwang.org/programming/opencv-basic-image-read-and-write-tutorial/
* https://blog.cavedu.com/2020/02/06/jetson-nano-01-webcam/
### **jetson.utils**
* https://cloud.tencent.com/developer/article/1845702
### **錯誤訊息**
* https://github.com/keras-team/keras-tuner/issues/317
* https://github.com/tensorflow/tensorflow/issues/26813
* https://hoohoo.top/blog/several-ways-to-solve-the-no-module-named-kerasmodels-error/
* https://github.com/pypa/virtualenv/issues/988
### **nvgstcapture-1.0**
* https://github.com/pauldotknopf/JetsonTX1Drivers/blob/master/nv_tegra/nv_sample_apps/nvgstcapture-1.0_README.txt
### **NVIDIA**
* https://developer.nvidia.com/embedded/learn/tutorials/first-picture-csi-usb-camera
### **jetson inference**
* https://github.com/dusty-nv/jetson-inference/blob/master/docs/aux-streaming.md
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