Update app.py

app.py

@@ -2,6 +2,7 @@ import torch
 import cv2
 import numpy as np
 import gradio as gr
+from PIL import Image
 
 
 model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
@@ -14,20 +15,23 @@ model.multi_label = False
 model.max_det = 1000
 
 
-img = gr.inputs.Image(shape=(192, 192))
+def detect(img):
 
 
-results = model(img, size=640)
+    results = model(img, size=640)
 
-predictions = results.pred[0]
-boxes = predictions[:, :4] # x1, y1, x2, y2
-scores = predictions[:, 4]
-categories = predictions[:, 5]
-annotated_image = np.squeeze(results.render())
+    predictions = results.pred[0]
+    boxes = predictions[:, :4] # x1, y1, x2, y2
+    scores = predictions[:, 4]
+    categories = predictions[:, 5]
+    new_image = npnp.squeeze(results.render())
+    print(new_image.shape)
+    return new_image
 
-outputs= plt.imshow(annotated_image)
+    
 
 
+img = gr.inputs.Image(shape=(192, 192))
 
-intf = gr.Interface(inputs=img, outputs=outputs)
-intf.launch(inline=False)
+#intf = gr.Interface(fn=detect, inputs=img, outputs='image')
+#intf.launch(inline=False)