Update app.py

app.py

@@ -1,20 +1,41 @@
 from huggingface_hub import from_pretrained_fastai
 import gradio as gr
-# from fastai.vision.all import *
-from fastai.text.all import *
+from fastai.vision.all import *
+from icevision.all import *
 
+# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
+repo_id = "igmarco/raccoon-image-detection"
 
+model1 = from_pretrained_fastai(repo_id)
 
-# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"
-repo_id = "igmarco/LSTM-text-classification"
-
-learner = from_pretrained_fastai(repo_id)
-labels = ['hate speech', 'offensive language', 'neither']
-
-# Definimos una función que se encarga de llevar a cabo las predicciones
-def predict(txt):
-    pred,pred_idx,probs = learner.predict(txt)
-    return {labels[i]: float(probs[i]) for i in range(len(labels))}
-    
-# Creamos la interfaz y la lanzamos. 
-gr.Interface(fn=predict, inputs=gr.Textbox(lines=2, placeholder="Text Here..."), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=False)
+def show_preds(input_image, display_label, display_bbox, detection_threshold):
+
+    if detection_threshold==0: detection_threshold=0.5
+
+    img = PIL.Image.fromarray(input_image, 'RGB')
+
+    pred_dict  = models.torchvision.faster_rcnn.end2end_detect(img, valid_tfms, model1, class_map=class_map, detection_threshold=detection_threshold,
+                                           display_label=display_label, display_bbox=display_bbox, return_img=True, 
+                                           font_size=16, label_color="#FF59D6")
+
+    return pred_dict['img']
+
+# display_chkbox = gr.inputs.CheckboxGroup(["Label", "BBox"], label="Display", default=True)
+display_chkbox_label = gr.inputs.Checkbox(label="Label", default=True)
+display_chkbox_box = gr.inputs.Checkbox(label="Box", default=True)
+
+detection_threshold_slider = gr.inputs.Slider(minimum=0, maximum=1, step=0.1, default=0.5, label="Detection Threshold")
+
+outputs = gr.outputs.Image(type="pil")
+
+# Option 1: Get an image from local drive
+gr_interface = gr.Interface(fn=show_preds, inputs=["image", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs,examples=['raccoon1.jpg','raccoon2.jpg'])
+
+# #  Option 2: Grab an image from a webcam
+# gr_interface = gr.Interface(fn=show_preds, inputs=["webcam", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs, title='IceApp - COCO', live=False)
+
+# #  Option 3: Continuous image stream from the webcam
+# gr_interface = gr.Interface(fn=show_preds, inputs=["webcam", display_chkbox_label, display_chkbox_box,  detection_threshold_slider], outputs=outputs, title='IceApp - COCO', live=True)
+
+
+gr_interface.launch(inline=False, share=False, debug=True)