add example into the demo

app.py

@@ -6,7 +6,21 @@ from torch import nn
 from torchvision import transforms
 from transformers import SegformerForSemanticSegmentation
 
+# examples
+os.system("wget -O 073.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/buenos_resultados/073.png")
+os.system("wget -O 356.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/buenos_resultados/356.png")
+os.system("wget -O 599.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/buenos_resultados/599.png")
+os.system("wget -O 630.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/buenos_resultados/630.png")
+os.system("wget -O 673.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/buenos_resultados/673.png")
 
+
+os.system("wget -O 019.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/malos_resultados/019.png")
+os.system("wget -o 261.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/malos_resultados/261.png")
+os.system("wget -o 524.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/malos_resultados/524.png")
+os.system("wget -o 716.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/malos_resultados/716.png")
+os.system("wget -o 898.png https://huggingface.co/spaces/alkzar90/rock-glacier-segmentation/resolve/main/example_images/malos_resultados/898.png")
+
+# model-setting
 MODEL_PATH="./best_model_mixto/"
 
 device = torch.device("cpu")
@@ -18,7 +32,7 @@ preprocessor = transforms.Compose([
 model = SegformerForSemanticSegmentation.from_pretrained(MODEL_PATH)
 model.eval()
 
-
+# inference-functions
 def upscale_logits(logit_outputs, size):
    """Escala los logits a (4W)x(4H) para recobrar dimensiones originales del input"""
    return nn.functional.interpolate(
@@ -53,13 +67,15 @@ def query_image(img):
     result = predict_label[0,:,:].detach().cpu().numpy()
     return visualize_instance_seg_mask(result)
 
-
+# demo
 demo = gr.Interface(
     query_image,
     inputs=[gr.Image(type="pil").style(full_width=True, height=256, width=256)],
     outputs=[gr.Image().style(full_width=True, height=256, width=256)],
     title="Skyguard: segmentador de glaciares de roca  🛰️ +️ 🛡️ ️",
-    description="Modelo de segmentación de imágenes para detectar glaciares de roca.<br> Se entrenó un modelo [nvidia/SegFormer](https://huggingface.co/nvidia/mit-b0) con _fine-tuning_ en el [rock-glacier-dataset](https://huggingface.co/datasets/alkzar90/rock-glacier-dataset)"
+    description="Modelo de segmentación de imágenes para detectar glaciares de roca.<br> Se entrenó un modelo [nvidia/SegFormer](https://huggingface.co/nvidia/mit-b0) con _fine-tuning_ en el [rock-glacier-dataset](https://huggingface.co/datasets/alkzar90/rock-glacier-dataset)",
+    examples=[["073.png", "356.png", "599.png", "630.png", "673.png", "019.png", "261.png", "524.png", "716.png", "898.png"]],
+    cache_examples=False
 )
 
 demo.launch()