Update plants example

examples/plant-classification/README.md

@@ -23,22 +23,21 @@ scar init -f scar-plant-classification.yaml
 2. Upload the processing script to Amazon S3
 
 ```sh
-scar put -b scar-test/scar-plant-classification -p plant-classification-run.sh
+scar put -b scar-test/scar-plants -p plant-classification-run.sh
 ```
 
 3. Upload an image to the input folder of the bucket (to trigger the image processing)
 
 ```sh
-wget https://upload.wikimedia.org/wikipedia/commons/thumb/c/ce/Daisy_G%C3%A4nsebl%C3%BCmchen_Bellis_perennis_01.jpg/640px-Daisy_G%C3%A4nsebl%C3%BCmchen_Bellis_perennis_01.jpg -O daisy.jpg
-scar put -b scar-test/scar-plant-classification/input -p daisy.jpg
+scar put -b scar-test/scar-plants/input -p daisy.jpg
 ```
 
 If you upload several files, the corresponding jobs will be submitted to AWS Batch. Depending on the number of jobs it may decide to spawn additional EC2 instances in order to cope with the increased workload. Once the executions have finished (you can check the corresponding CloudWatch logs) ...
 
 4. Download the generated files from the S3 bucket
 
 ```sh
-scar get -b scar-test/scar-plant-classification/output -p /tmp/plant-classification
+scar get -b scar-test/scar-plants/output -p /tmp/plant-classification
 ```
 
 The last command creates an `output/$REQUEST_ID` folder in the `/tmp/plant-classification` path with the files generated by each invocation.

scar/providers/aws/cloud/batch/Dockerfile

@@ -3,7 +3,7 @@ FROM python:3-alpine
 ENV SCAR_LOG_PATH='/var/log/'
 ENV SUPERVISOR_TYPE='BATCH'
 
-RUN apk add git && git clone --branch storage https://github.com/grycap/faas-supervisor && cd faas-supervisor && pip3 install -U .
+RUN pip3 install faas-supervisor
 
 COPY batch_handler.py batch_handler.py