The visualization is done using a model created in Lobe.
I tried to get a heatmap using the usage code but what was displayed was a slightly darkened original image.
from lobe import ImageModel
from PIL import Image
import os
import sys
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
mePath = os.path.dirname(file)
model = ImageModel.load('path/to/exported/model/folder')
img = Image.open('path/to/file.jpg')
result = model.predict(img)
img.show()
print(result.prediction)
for label, confidence in result.labels:
print(f"{label}: {confidence*100}%")
heatmap = model.visualize(img)
heatmap.show()
I added a sentence to display heatmap_img at line 162 of image_model.py to test it, and found that heatmap_img was completely dark.
The visualization is done using a model created in Lobe. I tried to get a heatmap using the usage code but what was displayed was a slightly darkened original image.
from lobe import ImageModel from PIL import Image import os import sys os.environ["CUDA_VISIBLE_DEVICES"] = "-1" mePath = os.path.dirname(file) model = ImageModel.load('path/to/exported/model/folder') img = Image.open('path/to/file.jpg') result = model.predict(img) img.show()
print(result.prediction)
for label, confidence in result.labels: print(f"{label}: {confidence*100}%")
heatmap = model.visualize(img) heatmap.show()
I added a sentence to display heatmap_img at line 162 of image_model.py to test it, and found that heatmap_img was completely dark.
heatmap_img = heatmap_img.resize((height, width)) heatmap_img .show()