- {% for image in images %}
+ {% for image in images|slice:":20" %}
-
-
diff --git a/elevate/lynx/views.py b/elevate/lynx/views.py
index 5580c61b9..8d3f7aaf5 100644
--- a/elevate/lynx/views.py
+++ b/elevate/lynx/views.py
@@ -12,36 +12,36 @@
import pytorch_lightning as pl
-
+ds=pd.read_csv('lynx/csv/custom.csv')
CLASSES = 25
classDic = {
- 0: 'CasualMen',
- 1: 'CasualWomen',
- 2: 'EthnicMen',
- 3: 'CasualBoys',
- 4: 'FormalMen',
- 5: 'CasualGirls',
- 6: 'CasualUnisex',
- 7: 'SportsMen',
- 8: 'EthnicWomen',
- 9: 'SportsWomen',
- 10: 'FormalWomen',
- 11: 'SportsUnisex',
- 12: 'SportsBoys',
- 13: 'Smart CasualWomen',
- 14: 'TravelUnisex',
- 15: 'Smart CasualMen',
- 16: 'PartyWomen',
- 17: 'EthnicBoys',
- 18: 'EthnicGirls',
- 19: 'TravelWomen',
- 20: 'HomeUnisex',
- 21: 'PartyMen',
- 22: 'SportsGirls',
- 23: 'TravelMen',
- 24: 'FormalUnisex'
+ 0: 'Casual Men',
+ 1: 'Casual Women',
+ 2: 'Ethnic Men',
+ 3: 'Casual Boys',
+ 4: 'Formal Men',
+ 5: 'Casual Girls',
+ 6: 'Casual Unisex',
+ 7: 'Sports Men',
+ 8: 'Ethnic Women',
+ 9: 'Sports Women',
+ 10: 'Formal Women',
+ 11: 'Sports Unisex',
+ 12: 'Sports Boys',
+ 13: 'Smart Casual Women',
+ 14: 'Travel Unisex',
+ 15: 'Smart Casual Men',
+ 16: 'Party Women',
+ 17: 'Ethnic Boys',
+ 18: 'Ethnic Girls',
+ 19: 'Travel Women',
+ 20: 'Home Unisex',
+ 21: 'Party Men',
+ 22: 'Sports Girls',
+ 23: 'Travel Men',
+ 24: 'Formal Unisex'
}
transformaciones = transforms.Compose([transforms.Resize((64,64)),
transforms.ToTensor(), #0 - 255--->0 - 1
@@ -208,44 +208,28 @@ def image_detail(request, image_name):
new_model =CNNModel()
new_model.load_state_dict(state)
-
+ #Obtengo la predicción de su clase
img = Image.open('lynx/static/'+image_name)
t_img = transformaciones(img).unsqueeze(0)
prediction = new_model.predict(t_img)
etiqueta=classDic[prediction.item()]
print('Valor predicho: ',etiqueta )
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- images = [
- {
- 'url': '/static/1163.jpg',
- 'name': 'Imagen 1',
- 'link': '/images/1',
- },
- {
- 'url': '/static/1535.jpg',
- 'name': 'Imagen 2',
- 'link': '/images/2',
- },
- {
- 'url': '/static/1571.jpg',
- 'name': 'Imagen 3',
- 'link': '/images/2',
- },
- ]
-
- return render(request, 'image_detail.html', {'images': images})
+ #Obtengo las imágenes que pertenecen a la misma clase
+ condicion_etiqueta = ds['target'] == prediction.item()
+ candidatas=ds[condicion_etiqueta]
+ print(candidatas)
+ imagenes=candidatas.image.unique()
+
+ images = []
+ for imagen in imagenes:
+ image = {
+ 'url': f'/static/images/{imagen}',
+ 'name': f'Imagen {imagen}',
+ 'link': f'/images/{imagen}',
+ }
+ images.append(image)
+
+
+ return render(request, 'image_detail.html', {'images': images, 'etiqueta': etiqueta})
diff --git a/requirements.txt b/requirements.txt
index 94a0e8344..882d6b82c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1 +1,9 @@
Django
+numpy
+torch
+pandas
+Pillow
+fastcore
+torchvision
+torchmetrics
+pytorch_lightning
\ No newline at end of file