Fixing multiagent with topdownmap #1072
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facebook-github-bot
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Skylion007
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Jan 10, 2023
…wn_map. (requires pygame installed and mac)
```
import habitat
import numpy as np
cli_arg = ['+habitat/task/measurements=top_down_map']
config = habitat.get_config('benchmark/rearrange/rearrange_easy_multi_agent.yaml', cli_arg)
from habitat.utils.gym_definitions import make_gym_from_config
env = make_gym_from_config(config)
env.reset();env.render()
while True:
_,_,_,_ = env.step(np.array(([0.0] * 8 + [0.2, 1.0] + [0.0]) + ([0.0] * 8 + [0.2, -1.0] + [0.0]) , dtype=np.float32))
_=env.render()
```
ASzot
approved these changes
Jan 11, 2023
Skylion007
approved these changes
Jan 11, 2023
dannymcy
pushed a commit
to dannymcy/habitat-lab
that referenced
this pull request
Jul 8, 2024
* render now will render the top_down_map properly
* made topdown map work for rearrangement
* working for rearrangement
* Adding agent_index to action configurations'
* addressing comments and removing the top_down_map from the default measures
* For reference, run this code to see the multi-agent render the top_down_map. (requires pygame installed and mac)
```
import habitat
import numpy as np
cli_arg = ['+habitat/task/measurements=top_down_map']
config = habitat.get_config('benchmark/rearrange/rearrange_easy_multi_agent.yaml', cli_arg)
from habitat.utils.gym_definitions import make_gym_from_config
env = make_gym_from_config(config)
env.reset();env.render()
while True:
_,_,_,_ = env.step(np.array(([0.0] * 8 + [0.2, 1.0] + [0.0]) + ([0.0] * 8 + [0.2, -1.0] + [0.0]) , dtype=np.float32))
_=env.render()
```
* unifying extract_scalar_info
* proper typing for rgb_frame
* resolving one last issue
* resolving issues with set_agent_state in rearrangement
Co-authored-by: vincentpierre <vincentpierre@users.noreply.github.com>
HHYHRHY
pushed a commit
to SgtVincent/EMOS
that referenced
this pull request
Aug 31, 2024
* render now will render the top_down_map properly
* made topdown map work for rearrangement
* working for rearrangement
* Adding agent_index to action configurations'
* addressing comments and removing the top_down_map from the default measures
* For reference, run this code to see the multi-agent render the top_down_map. (requires pygame installed and mac)
```
import habitat
import numpy as np
cli_arg = ['+habitat/task/measurements=top_down_map']
config = habitat.get_config('benchmark/rearrange/rearrange_easy_multi_agent.yaml', cli_arg)
from habitat.utils.gym_definitions import make_gym_from_config
env = make_gym_from_config(config)
env.reset();env.render()
while True:
_,_,_,_ = env.step(np.array(([0.0] * 8 + [0.2, 1.0] + [0.0]) + ([0.0] * 8 + [0.2, -1.0] + [0.0]) , dtype=np.float32))
_=env.render()
```
* unifying extract_scalar_info
* proper typing for rgb_frame
* resolving one last issue
* resolving issues with set_agent_state in rearrangement
Co-authored-by: vincentpierre <vincentpierre@users.noreply.github.com>
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Motivation and Context
On top of making TopDownMap work for rearrangement tasks, I also added an agent_index to the actions allowing to control the agents from the gym interface. Running this code :
Gives the following pygame output :
How Has This Been Tested
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