Darkflow: Outputting images with bounding boxes instead of JSON like result

[idhamhalim]

So. I tried the code for using darkflow from another python application, I modified it , because I wanted it to return multiple images with bounding box, however the output only returns predictions and is returned in a JSON-like format. How do i return it in form of images with the bounding boxes

`from darkflow.net.build import TFNet
from os import listdir
from os.path import isfile, join
import numpy
import cv2

options = {"model": "cfg/tiny-yolo-voc.cfg", "load": "tiny-yolo-voc.weights", "threshold": 0.1}

tfnet = TFNet(options)

mypath='/home/idham/darkflow-trial/image'
onlyfiles = [ f for f in listdir(mypath) if isfile(join(mypath,f)) ]
images = numpy.empty(len(onlyfiles), dtype=object)

for n in range(0, len(onlyfiles)):

    images[n] = cv2.imread( join(mypath,onlyfiles[n]) )
    result = tfnet.return_predict(images[n])
    print(result)`

some of the results :

[{'topleft': {'x': 469, 'y': 379}, 'label': 'bottle', 'confidence': 0.18183012, 'bottomright': {'x': 615, 'y': 687}}, {'topleft': {'x': 570, 'y': 439}, 'label': 'bottle', 'confidence': 0.35135984, 'bottomright': {'x': 705, 'y': 719}}, {'topleft': {'x': 664, 'y': 458}, 'label': 'bottle', 'confidence': 0.22756532, 'bottomright': {'x': 825, 'y': 715}}, {'topleft': {'x': 503, 'y': 568}, 'label': 'bottle', 'confidence': 0.18111153, 'bottomright': {'x': 581, 'y': 711}}, {'topleft': {'x': 588, 'y': 559}, 'label': 'bottle', 'confidence': 0.14755477, 'bottomright': {'x': 674, 'y': 719}}, {'topleft': {'x': 689, 'y': 563}, 'label': 'bottle', 'confidence': 0.13069168, 'bottomright': {'x': 788, 'y': 717}}, {'topleft': {'x': 213, 'y': 563}, 'label': 'diningtable', 'confidence': 0.13041878, 'bottomright': {'x': 467, 'y': 704}}]

[ssusie]

When you run, for example,

_flow --imgdir sample_img/ --model cfg/tiny-yolo.cfg --load bin/tiny-yolo.weights --json_

it return json files, however if instead you just run

_flow --imgdir sample_img/ --model cfg/tiny-yolo.cfg --load bin/tiny-yolo.weights_

it outputs images with bounding boxes.

[idhamhalim]

@

[lijiaze2018]

@idhamhalim Hello friends, have you solved this problem?

[idhamhalim]

It's already solved.

[lijiaze2018]

@idhamhalim So can you tell me how to do it? I can only do the output of the json file, but I want to get the predicted result graph by running the py file directly (that is, the same effect as the cmd run), your help is very important to me, thank you!

[YasserTahaSW]

@lijiaze2018
check @ssusie's comment.

[Wanderish]

@idhamhalim were you able to do what @ssusie said from inside a py script or did you want it just from the terminal?

[idhamhalim]

Hi guys,

You can try look at my repo, and see predictidham.py script. That script is
configured to save images that are labelled with car in the video. You can
try to change labels to another value, but you do need to check which
labels are available.

Repo link below.
https://github.com/idhamhalim/image-recognition-detection/blob/master/predict-idham.py

On Mon, 22 Apr 2019, 15:12 Shreyas Dixit, [e-mail] wrote:

@idhamhalim https://github.com/idhamhalim were you able to do what
@ssusie https://github.com/ssusie said from inside a py script or did
you want it just from the terminal?

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