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Vearch is aimed to build a simple and fast image retrieval system. Through this system, you can easily build your own image retrieval system, including image object detection, feature extraction and similarity search. This quickstart demonstrates how to use it.
And you can download coco data for testing, or use the images in images folder we choose from coco data.
This requires only two operations:
ip_address in config/config.py;run.sh;Before inserting and searching, you should create a database and space. Use the following curl command to create a new database and space.
curl -XPOST -H "content-type:application/json" -d '{
"db": true,
"method": "innerproduct",
"columns": {
"imageurl": {
"type": "keyword"
},
"boundingbox": {
"type": "keyword"
},
"label": {
"type": "keyword"
}
},
"feature": {
"type": "vector",
"filed": "imageurl",
"model_id": "vgg16",
"dimension": 512
}
}' http://{ip}:{port}/test/test/_create
A successful response looks like this:
{"code": 200, "db_msg": "success", "space_msg": "success"}
If you want delete a database and space. Use the following curl command to delete a database and space
curl -XPOST -H "content-type:application/json" -d '{
"db": false,
"space": true
}' http://{ip}:{port}/test/test/_delete
A successful response looks like this:
{"code": 200, "db_msg": "success", "space_msg": "success"}
We support both single and bulk imports. Use the following curl command to insert single data into space.
The method of single import demo:
# single insert
curl -XPOST -H "content-type:application/json" -d '{
"imageurl": "images/test/COCO_val2014_000000123599.jpg",
"detection": false,
"boundingbox": "10,10,290,290",
"label": "coat"
}' http://{ip}:{port}/test/test/_insert
The method of bulk import demo:
# bulk insert
curl -XPOST -H "content-type:application/json" -d '{
"method": "bulk",
"imageurl": "./images/test.csv",
"detection": true
}' http://{ip}:{port}/test/test/_insert
A successful response like this:
# response
{
"db": "test",
"space": "test",
"ids": [
{
"AWz2IRAvJG6WicwQVToi": "successful"
},
{
"AWz2IRFVJG6WicwQVTom": "successful"
},
{
"AWz2IRJyJG6WicwQVToq": "successful"
},
{
"AWz2IRDEJG6WicwQVTok": "successful"
},
{
"AWz2IRHlJG6WicwQVToo": "successful"
},
{
"AWz2IRMGJG6WicwQVTos": "successful"
},
{
"AWz2IRQpJG6WicwQVTow": "successful"
},
{
"AWz2IROaJG6WicwQVTou": "successful"
},
{
"AWz2IRTQJG6WicwQVToy": "successful"
},
{
"AWz2IRVhJG6WicwQVTo0": "successful"
}
],
"successful": 10
}
Use the following curl command to get a record by ID
# request
curl -XGET http://{ip}:{port}/test/test/AWz2IFBSJG6WicwQVTog
# response
{
"_index": "test",
"_type": "test",
"_id": "AWz2IFBSJG6WicwQVTog",
"found": true,
"_version": 1,
"_source": {
"boundingbox": '232,204,436,406',
"imageurl": "images/test/COCO_val2014_000000123599.jpg",
"label": "zebra"
}
}
Use the following curl command to delete a record by ID
# request
curl -XDELETE http://{ip}:{port}/test/test/AWz2IFBSJG6WicwQVTog
# response
{
"code": 200,
"msg": "success"
}
Use the following curl command to update a record by ID
# request
curl -XPOST -H "content-type:application/json" -d '{
"imageurl": "images/test/COCO_val2014_000000123599.jpg",
"detection": true
}' http://{ip}:{port}/test/test/_update?id=AWz2IFBSJG6WicwQVTog
# response
{
"db": "test",
"space": "test",
"ids": [
{
"AWz2IFBSJG6WicwQVTog": "successful"
}
],
"successful": 1
}
You can search using a base64 encoded local image, or use an image URI for an publicly accessible online image or an image stored in images folders.
Search using an image stored in images folders or image URI on Internet. Use the following curl command to search similar result from space
curl -XPOST -H "content-type:application/json" -d '{
"imageurl": "images/test/COCO_val2014_000000123599.jpg",
"detection": true,
"score": 0.5,
"filter": [
{
"term": {
"label": {
"value": "zebra"
}
}
}
],
"size": 5
}' http://{ip}:{port}/test/test/_search
or you can simply use the following curl command:
curl -XPOST -H "content-type:application/json" -d '{
"imageurl": "images/test/COCO_val2014_000000123599.jpg"
}' http://{ip}:{port}/test/test/_search
A successful response looks like this:
{
'took': 9,
'timed_out': False,
'_shards': {
'total': 1,
'failed': 0,
'successful': 1
},
'hits': {
'total': 14068,
'max_score': 0.9999999403953552,
'hits': [
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_ciUvJG6WicwQQgXP',
'_score': 0.9999999403953552,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000123599.jpg',
'score': 0.9999999403953552
}
]
},
'_version': 1,
'_source': {
'boundingbox': '35,
67,
546,
556',
'imageurl': 'images/test/COCO_val2014_000000123599.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_bVB0JG6WicwQQfbh',
'_score': 0.9116669297218323,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000095375.jpg',
'score': 0.9116669297218323
}
]
},
'_version': 1,
'_source': {
'boundingbox': '34,
320,
208,
427',
'imageurl': 'images/test/COCO_val2014_000000095375.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_ZKBpJG6WicwQQdxL',
'_score': 0.9110268354415894,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000045535.jpg',
'score': 0.9110268354415894
}
]
},
'_version': 1,
'_source': {
'boundingbox': '218,
171,
494,
346',
'imageurl': 'images/test/COCO_val2014_000000045535.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_XbS-JG6WicwQQccF',
'_score': 0.9091571569442749,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000007522.jpg',
'score': 0.9091571569442749
}
]
},
'_version': 1,
'_source': {
'boundingbox': '232,
204,
436,
406',
'imageurl': 'images/test/COCO_val2014_000000007522.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_dFBwJG6WicwQQgyR',
'_score': 0.9059789180755615,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000136077.jpg',
'score': 0.9059789180755615
}
]
},
'_version': 1,
'_source': {
'boundingbox': '288,
75,
624,
285',
'imageurl': 'images/test/COCO_val2014_000000136077.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_YQzVJG6WicwQQdFf',
'_score': 0.9054344296455383,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000026174.jpg',
'score': 0.9054344296455383
}
]
},
'_version': 1,
'_source': {
'boundingbox': '191,
89,
506,
388',
'imageurl': 'images/test/COCO_val2014_000000026174.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_ajGhJG6WicwQQe0v',
'_score': 0.9029231071472168,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000077479.jpg',
'score': 0.9029231071472168
}
]
},
'_version': 1,
'_source': {
'boundingbox': '110,
82,
525,
391',
'imageurl': 'images/test/COCO_val2014_000000077479.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_Y3-bJG6WicwQQdjf',
'_score': 0.9010977745056152,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000039390.jpg',
'score': 0.9010977745056152
}
]
},
'_version': 1,
'_source': {
'boundingbox': '0,
141,
187,
290',
'imageurl': 'images/test/COCO_val2014_000000039390.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_YJpVJG6WicwQQc_t',
'_score': 0.8993719816207886,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000023411.jpg',
'score': 0.8993719816207886
}
]
},
'_version': 1,
'_source': {
'boundingbox': '238,
89,
538,
390',
'imageurl': 'images/test/COCO_val2014_000000023411.jpg',
'label': 'zebra'
}
},
{
'_index': 'test',
'_type': 'test',
'_id': 'AWz_fDU9JG6WicwQQiTB',
'_score': 0.8990296721458435,
'_extra': {
'vector_result': [
{
'field': 'feature',
'source': 'images/test/COCO_val2014_000000180363.jpg',
'score': 0.8990296721458435
}
]
},
'_version': 1,
'_source': {
'boundingbox': '36,
88,
335,
310',
'imageurl': 'images/test/COCO_val2014_000000180363.jpg',
'label': 'zebra'
}
}
]
}
}
search result look like this
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