Recover Image

Documents: https://drive.google.com/file/d/1O_pAM29H1FgaSKmwSrVF2Wna9Q4tEtRA/view

Input Image:

Recovery Image:

Install Python Libraries

pip install -r requirements.txt

Data Source

https://github.com/openimages/dataset/blob/main/READMEV3.md

How to run code

Pull image from server

usage: interaction.py [-h] [--sol-path SOL_PATH] [--output-path OUTPUT_PATH] [--token TOKEN]
                      [-s TOURNAMENT_NAME] [-r ROUND_NAME] [-m MATCH_NAME] [-p MODE]

optional arguments:
  -h, --help            show this help message and exit
  --sol-path SOL_PATH
  --output-path OUTPUT_PATH
  --token TOKEN
  -s TOURNAMENT_NAME, --tournament_name TOURNAMENT_NAME
  -r ROUND_NAME, --round_name ROUND_NAME
  -m MATCH_NAME, --match_name MATCH_NAME
  -p MODE, --mode MODE [r/read, w/submmit, show]

Example:

python3 interaction.py --token 'abc' -s 'Tournament_1' -r 'Round_1' -m 'Match_1' -p 'r'

---

NOTE

Check ENDPOINT in src/request.py file.

---

The Match_1's information 'Match_1' saved on input/game_info/Match_1.json includes:

1. Block dimentions
2. Block size
3. original block
4. max number of selects
5. ratio of select and swap operator
6. image size

Image Recovery

usage: recover_image.py [-h] [--game-info-path GAME_INFO_PATH] [--model-path MODEL_PATH]
                        [--model-name MODEL_NAME] [--output-path OUTPUT_PATH] [-f FILE_NAME]
                        [--image-size-out IMAGE_SIZE_OUT] [-s BLOCK_SIZE] [-a ALGORITHM] [-v] [-m]
                        [-t THRESHOLD] [-j N_JUMPS]

optional arguments:
  -h, --help            show this help message and exit
  --game-info-path GAME_INFO_PATH
  --model-path MODEL_PATH
  --model-name MODEL_NAME
  --output-path OUTPUT_PATH
  -f FILE_NAME, --file-name FILE_NAME
  --image-size-out IMAGE_SIZE_OUT
  -a ALGORITHM, --algorithm ALGORITHM
  -v, --verbose         save every on output/sample.png file
  -m, --monitor         for interfere

Example:

python3 recover_image.py -f Match_1 -v -m

Recovery solution are stored in input/states/Match_1.bin binary file

Image Sorting

usage: procon.py [-h] [--state-path STATE_PATH] [-f ITEM_NAME] [--model-name MODEL_NAME]
                 [--output-path OUTPUT_PATH] [-a ALGORITHM] [-v] [-t SLEEP] [-k SKIP] [-s N_FAST_MOVES]
                 [-r RATE] [-c MAX_SELECT] [-d DEPTH] [-b BREADTH]

optional arguments:
  -h, --help            show this help message and exit
  --state-path STATE_PATH
  -f ITEM_NAME, --item-name ITEM_NAME
  --model-name MODEL_NAME
  --output-path OUTPUT_PATH
  -a ALGORITHM, --algorithm ALGORITHM
                        algorithm to use
  -v, --verbose
  -t SLEEP, --sleep SLEEP
  -k SKIP, --skip SKIP
  -s N_FAST_MOVES, --n_fast_moves N_FAST_MOVES
  -r RATE, --rate RATE
  -c MAX_SELECT, --max_select MAX_SELECT
  -d DEPTH, --depth DEPTH               (using for tree search)
  -b BREADTH, --breadth BREADTH         (using for tree search)

Example

python3 procon.py -f 'Match_1' -a 'standard' -s 1 -v 

Solution are stored in 'output/solutions/Match_1.json'

Finally, run this command to submit solution:

python3 interaction.py --token 'abc' -s 'Tournament_1' -r 'Round_1' -m 'Match_1' -p 'w'

Server return:

{
    'message': 'Invalid Solution/Submit solution success', 
    'cost': 10, 
    'correctPosition': 10, 
    'correctAngle': 10
}

Show all submissions:

python3 interaction.py --token 'abc' -s 'Tournament_1' -r 'Round_1' -m 'Match_1' -p 'show'