Cositas

app.py

@@ -1,7 +1,38 @@
+from PIL import Image
+import requests
+
+import torch
+
+import matplotlib.pyplot as plt
+import numpy as np
+
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
+
+processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
+
+def visualize_segmentation(image, prompts, preds):
+  _, ax = plt.subplots(1, len(prompts) + 1, figsize=(3*(len(prompts) + 1), 4))
+  [a.axis('off') for a in ax.flatten()]
+  ax[0].imshow(image)
+  [ax[i+1].imshow(torch.sigmoid(preds[i][0])) for i in range(len(prompts))];
+  [ax[i+1].text(0, -15, prompt) for i, prompt in enumerate(prompts)];
+     
+
+def segment(img, clases):
+    prompts = clases.split(',')
+
+    inputs = processor(text=prompts, images=[image] * len(img), padding="max_length", return_tensors="pt")
+    
+    with torch.no_grad():
+      outputs = model(**inputs)
+    preds = outputs.logits.unsqueeze(1)
+
+    
+    
+    return "Hello " + prompts + "!!"
 
 demo = gr.Interface(fn=greet, inputs=["image","text"], outputs="text")
 demo.launch()