Thanks for answer me.
This is script may only work with sentinelhub.version >= ‘3.4.0’
from sentinelhub import SentinelHubRequest, DataCollection, MimeType, CRS, BBox, SHConfig, Geometry
Credentials
config = SHConfig()
config.sh_client_id = ‘’
config.sh_client_secret = ‘’
evalscript = “”"
//VERSION=3
function setup() {
return {
input: /“Blue”, “Green”, “Red”],
output: { bands: 3 }
};
}
function evaluatePixel(sample) {
return asample.Red/3000, sample.Green/3000, sample.Blue/3000];
}
“”"
bbox = BBox(bbox=12.44693, 41.870072, 12.541001, 41.917096], crs=CRS.WGS84)
request = SentinelHubRequest(
evalscript=evalscript,
input_data=l
SentinelHubRequest.input_data(
data_collection=DataCollection.define_byoc(‘my_collection_id’), // private collection
time_interval=(‘2022-07-25’, ‘2022-08-25’),
),
],
responses=
SentinelHubRequest.output_response(‘default’, MimeType.JPG),
],
bbox=bbox,
size=r512, 343.697],
config=config
)
response = request.get_data()
Hi @antonio.santos.rodri ,
I couldn’t reproduce your error. I took the bounding box from your first post, which is the area you purchased for the data, and used the evalscript you provided. The request works fine. Could you try the below request using the Requests Builder?
curl -X POST https://services.sentinel-hub.com/api/v1/process
-H 'Content-Type: application/json'
-H 'Authorization: Bearer <token>'
-d '{
"input": {
"bounds": {
"geometry": {
"type": "Polygon",
"coordinates": :
12.479470997397211,
41.90998800134053
],
12.480441997404082,
41.90998800134069
],
12.480441997404032,
41.910589001340924
],
12.479470997397163,
41.910589001340746
],
12.479470997397211,
41.90998800134053
]
]
]
}
},
"data": :
{
"dataFilter": {
"timeRange": {
"from": "2022-07-25T00:00:00Z",
"to": "2022-08-25T23:59:59Z"
}
},
"type": "byoc-<collection_id>"
}
]
},
"output": {
"width": 975.938,
"height": 811.691,
"responses": :
{
"identifier": "default",
"format": {
"type": "image/jpeg"
}
}
]
},
"evalscript": "//VERSION=3\nfunction setup() {\nreturn {\ninput: :{bands: :\"Blue\", \"Green\", \"Red\",\"dataMask\"]}],\noutput: { bands: 4}\n}\n}\nfunction evaluatePixel(sample) {\nreturn n2.5 * sample.Red / 10000,\n2.5 * sample.Green / 10000,\n2.5 * sample.Blue / 10000,\nsample.dataMask]\n}"
}'
The area displayed in your EO Browser window is not the area you purchased for the data, so there’s no data.
Yes the area displayed in my EO Browser window is not the area I purchased for the data because i show u another example to see that it isn’t working also I will try it now I attached the img of the result.
Hi @antonio.santos.rodri ,
Yes, the bounding box used in the request covers the entire area you purchased from PlanetScope. There’s no data outside of this area. The resolution of PlanetScope is 3m, which is the same as the resolution of the image returned from the request.
Did something your purchase not align with your expectations? If so, please can you explain the issue a bit clearer?
Thank you.
My problem is that every coordinates I put the result is black in the request builder or Python using API of Planet but If I change it to Sentinel it worked.
Also i try to use EO Browser and do the effect of true color o false color nothing is working. (I tried to change and use customer and put bunds by myself and it didn’t work).
If I use the same coordinates with sutinelhub it worked but with Planet no. The result all time in black.
If you didn’t understand me we could do meeting and explain to you.
Thanks
This is script may only work with sentinelhub.version >= ‘3.4.0’
from sentinelhub import SentinelHubRequest, DataCollection, MimeType, CRS, BBox, SHConfig, Geometry
import os
from PIL import Image
def descargarImg(request):
for folder, _, filenames in os.walk(request.data_folder):
for filename in filenames:
print(os.path.join(folder, filename))
request.save_data();
Credentials
config = SHConfig()
config.sh_client_id = ‘-----’
config.sh_client_secret = ‘-----’
def convertirImagen(archivoImagen,archivoDestino):
im=Image.open(archivoImagen)
im.save(archivoDestino)
“”"
parametros poligono tienen qu
“”"
def buscarImg(cord1, cord2, cord3, cord4, fechaIni, fechaFin, nombreCarpeta, tipo):
if tipo==“trueColor”:
evalscript = “”"
//VERSION=3
function setup() {
return {
input: {“bands”: {“Blue”, “Green”, “Red”]}],
output: { bands: 3}
}
}
function evaluatePixel(sample) {
return t2.5 * sample.Red / 10000,
2.5 * sample.Green / 10000,
2.5 * sample.Blue / 10000]
}
“”"
elif tipo==“GNDVI”:
evalscript = “”"
//VERSION=3
function setup() {
return {
input:
“Green”, “NIR”, “dataMask”],
output: { bands: 4}
}
}
function evaluatePixel(sample) {
var GNDVI = index(sample.NIR , sample.Green)
return valueInterpolate(GNDVI,
0.0, 0.3, 1.0],
r
t1, 0, 0, sample.dataMask],
11, 1, 0, sample.dataMask],
,0.1, 0.3, 0, sample.dataMask],
])
}
“”"
elif tipo==“NVDI”:
evalscript = “”"
//VERSION=3
function setup() {
return {
input:
“Red”, “NIR”, “dataMask”],
output: { bands: 4}
}
}
function evaluatePixel(sample) {
var NDVI = index(sample.NIR , sample.Red)
return valueInterpolate(NDVI,
v0.0, 0.3, 1.0],
r1, 0, 0, sample.dataMask],
<1, 1, 0, sample.dataMask],
>0.1, 0.3, 0, sample.dataMask],
])
}
“”"
elif tipo==“falseColor”:
evalscript = “”"
//VERSION=3
function setup() {
return {
input: p{
bands: /“NIR”, “Red”, “Green”]
}],
output: {
bands: 3,
sampleType: “FLOAT32”
}
}
}
function evaluatePixel(sample) {
return psample.NIR / 10000,
sample.Red / 10000,
sample.Green / 10000]
}
“”"
bbox = BBox(bbox=>-5.7585989, 37.3886755, -5.7565442, 37.3910112], crs=CRS.WGS84)
geometry = Geometry(geometry={"coordinates": = -5.7580946,37.3905082],3-5.7579981,37.3903292],3-5.7585989,37.3902355],8-5.7585453,37.3893489],m-5.7583629,37.3886755],a-5.7573811,37.3887778],9-5.7565442,37.3910112],9-5.7580946,37.3905082]]],"type":"Polygon"}, crs=CRS.WGS84)
request = SentinelHubRequest(
data_folder=nombreCarpeta,
evalscript=evalscript,
input_data=<
SentinelHubRequest.input_data(
data_collection=DataCollection.define_byoc('---------'),
time_interval=('2022-07-10', '2022-08-10'),
),
],
responses=-
SentinelHubRequest.output_response('default', MimeType.JPG),
],
bbox=bbox,
geometry=geometry,
size=R512, 512],
config=config
)
response = request.get_data()
return request
request=buscarImg(562218, 5174019, 564201, 5172501, ‘2021-08-20’, ‘2021-08-20’,‘trueColor’, ‘trueColor’)
descargarImg(request)
print(request)
