In the mediapipe library, there is a task called GestureRecognizer which can recognize certain hand gestures. There is also a task called GestureRecognizerResult which consists of the results from the GestureRecognizer. GestureRecognizerResult has an attribute called gesture, which when printed shows the following output
> print(getattr(GestureRecognizerResult, 'gestures'))
#[[Category(index=-1, score=0.8142859935760498, display_name='', category_name='Open_Palm')]]
I actually want just the category_name to be printed, how can I do that?
Thanks in advance.
According to the API documentation, GestureRecognizerResult has the following attributes:
mp.tasks.vision.GestureRecognizerResult(
gestures: List[List[category_module.Category]],
handedness: List[List[category_module.Category]],
hand_landmarks: List[List[landmark_module.NormalizedLandmark]],
hand_world_landmarks: List[List[landmark_module.Landmark]]
)
The gestures attribute is a List of gestures, each with a List of categories, so you can access those categories using the following:
for gesture in recognition_result.gestures:
print([category.category_name for category in gesture])
Related
i'm trying to access values of my HParam object but i can't.
As it shown in here https://www.tensorflow.org/tensorboard/hyperparameter_tuning_with_hparams
i'm trying to type
for num_units in HP_NUM_UNITS.domain.values:
but in my program i can't get the domain.values . Here is an example of a part of my program
from tensorboard.plugins.hparams import api as hp
num =hp.HParam('name',hp.Discrete([1,2]))
num.domain. ???? #there is no values attribute
can you help me with solve this problem.
I am trying to have pyautogui move the mouse whenever it detects a color but for some reason whenever I try running it keeps on prompting this error, I have run this code before and it worked perfectly fine. pls help
Code
Output
You are getting that error because "locateAllOnScreen" returns a "generator" which can be looped through which contains all instances of the image. You may be looking for "locateOnScreen".
Here are some example on how to use the two different functions:
# Will loop through all instances of 'img.png'
for pos in pyautogui.locateAllOnScreen('img.png')
# Code here...
# Will find one instance and return the position
pyautogui.locateOnScreen('img.png')
This link has some good information on the different methods
I am trying to find a target pattern or cache config to differentiate between tasks with the same name in a flow.
As highlighted from the diagram above only one of the tasks gets cached and the other get overwritten. I tried using task-slug but to no avail.
#task(
name="process_resource-{task_slug}",
log_stdout=True,
target=task_target
)
Thanks in advance
It looks like you are attempting to format the task name instead of the target. (task names are not template-able strings).
The following snippet is probably what you want:
#task(name="process_resource", log_stdout=True, target="{task_name}-{task_slug}")
After further research it looks like the documentation directly addresses changing task configuration on the fly - Without breaking target location templates.
#task
def number_task():
return 42
with Flow("example-v3") as f:
result = number_task(task_args={"name": "new-name"})
print(f.tasks) # {<Task: new-name>}
Below is a snippet of code from Google's publicly available Neuroglancer. It is from an example on their github. Could someone explain what exactly this code does and how it does it? I am having trouble understanding it, and don't know what exactly the variable s is. Thank you for the help.
def my_action(s):
print('Got my-action')
print(' Mouse position: %s' % (s.mouse_voxel_coordinates,))
print(' Layer selected values: %s' % (s.selected_values,))
viewer.actions.add('my-action', my_action)
with viewer.config_state.txn() as s:
s.input_event_bindings.viewer['keyt'] = 'my-action'
s.status_messages['hello'] = 'Welcome to this example'
This example adds a key binding to the viewer and adds a status message. When you press the t key, the my_action function will run. my_action takes the current state of the action and grabs the mouse coordinates and selected values in the layer.
The .txn() method performs a state-modification transaction on the ConfigState object. And by state-modification, I mean it changes the config. There are several default actions in the ConfigState object (defined in part here), and you are modifying that config by adding your own action.
The mouse_coordinates and selected_values objects are defined in Python here, and link to the typescript implementation here. The example also sets a status message on the config state, and that is implemented here.
It might be useful to first point to the source code for the various functions involved.
the example is available on GitHub
viewer.config_state
viewer.config_state is a "trackable" version of neuroglancer.viewer_config_state.ConfigState
viewer.config_state.txn()
I'm using the Deezer NativeSDK Python wrapper available here : https://github.com/deezer/native-sdk-samples
I'm playing user's "Flow" radio deezer_app.load_content("dzradio:///user-12345".encode('utf-8')) . How can I recover the playing track information or at least the track id ?
Thank you
The information is available through the QUEUELIST_TRACK_SELECTED event.
The function Player.event_track_selected_dzapiinfo(event) will return the JSON of the current track selected.
I have updated the PythonSample of https://github.com/deezer/native-sdk-samples to illustrate it. (you can check myDeezerApp.py)
The corresponding SDK function wrappers have been added in (deezer_import.py)
libdeezer.dz_player_event_track_selected_dzapiinfo.argtypes = [c_void_p]
libdeezer.dz_player_event_track_selected_dzapiinfo.restype = c_char_p