When I am uploading a picture to check a picture according to tensorflow h5 model, I am loading the image using load_model of tensorflow.keras.models but it is not accepting. For JPG, it is showing TypeError: expected str, bytes or os.PathLike object, not JpegImageFile and for PNG, it is showing as TypeError: expected str, bytes or os.PathLike object, not PngImageFile. What to do now?
I tried the code with raw python but it worked nicely.
Code:
#views.py
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
pic = request.FILES['image']
img = Image.open(pic)
detection=load_model(os.path.join(settings.BASE_DIR,'static/auto_chloro_model.h5'))
test_img=image.load_img(img,target_size=(48,48))
test_img=image.img_to_array(test_img)
test_img=np.expand_dims(test_img,axis=0)
result=detection.predict(test_img)
a=result.argmax()
print(a)
#models.py
class images(models.Model):
img_main = models.ImageField(upload_to="images_api", default="")
def __str__(self):
return self.product_name
#forms.py
class imageForm(forms.ModelForm):
image = forms.ImageField()
class Meta:
model = images
fields = ['image']
Traceback:
Traceback (most recent call last):
File "C:Usersjoyan.condaenvstensorflow-djangolibsite-packagesdjangocorehandlersexception.py", line 47, in inner
response = get_response(request)
File "C:Usersjoyan.condaenvstensorflow-djangolibsite-packagesdjangocorehandlersbase.py", line 181, in _get_response
response = wrapped_callback(request, *callback_args, **callback_kwargs)
File "H:Projects + Programming ProjectsAuto Chloroplantdetectionviews.py", line 50, in uploadImage
test_img=image.load_img(img,target_size=(48,48))
File "C:Usersjoyan.condaenvstensorflow-djangolibsite-packageskeras_preprocessingimageutils.py", line 113, in load_img
with open(path, 'rb') as f:
TypeError: expected str, bytes or os.PathLike object, not JpegImageFile```
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Answer
This solved my problem.
pic = request.FILES['image'] img_new = images(img_main= pic) img_new.save() detection=load_model(os.path.join(settings.BASE_DIR,'staticfiles/auto_chloro_model.h5')) test_img=image.load_img(img_new.img_main.path,target_size=(48,48)) test_img=image.img_to_array(test_img) test_img=np.expand_dims(test_img,axis=0) result=detection.predict(test_img) a=result.argmax()