Update app.py

app.py

@@ -118,6 +118,51 @@ def predict(img):
     # Return the prediction dictionary and prediction time 
     return pred_labels_and_probs, pred_time
 
+
+def show_preds_video(video_path):
+    cap = cv2.VideoCapture(video_path)
+    while(cap.isOpened()):
+        ret, frame = cap.read()
+        if ret:
+            frame_copy = frame.copy()
+            pix=model.predict(frame, confidence=40, overlap=30)
+            pix=pix.json()
+            x1,x2,y1,y2=[],[],[],[]
+            for i in pix.keys():
+                if i=="predictions":
+                    for j in pix["predictions"]:
+                        for a,b in j.items():
+                            if a=="x":
+                                x1.append(b)
+                            if a=="y":
+                                y1.append(b)
+                            if a=="width":
+                                x2.append(b)
+                            if a=="height":
+                                y2.append(b)
+
+
+
+            for p in range(0,len(x1)):
+                x2[p]=x2[p]+x1[p]
+
+            for p in range(0,len(x1)):
+                y2[p]=y2[p]+x1[p]
+
+            for (x11,y11,x12,y12) in zip(x1,y1,x2,y2):
+                cv2.rectangle(
+                        img,
+                        (x11,y11),
+                        (x12,y12),
+                        color=(0, 0, 255),
+                        thickness=2,
+                        lineType=cv2.LINE_AA
+                    )
+
+            
+            yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
+
+
 ### 4. Gradio app ###
 
 # Create title, description and article strings
@@ -136,6 +181,16 @@ outputs_image = [
     gr.components.Image(type="numpy", label="Output Image"),
 ]
 
+
+inputs_video = [
+    gr.components.Video(type="filepath", label="Input Video"),
+
+]
+outputs_video = [
+    gr.components.Image(type="numpy", label="Output Image"),
+]
+
+
 # Create the Gradio demo
 app1 = gr.Interface(fn=predict, # mapping function from input to output
                     inputs=gr.Image(type="pil"), # what are the inputs?
@@ -152,8 +207,15 @@ app2=gr.Interface(fn=detect,
                  inputs=inputs_image,
                  outputs=outputs_image,
                  title=title)
+app3=gr.Interface(
+    fn=show_preds_video,
+    inputs=inputs_video,
+    outputs=outputs_video,
+    examples=video_path,
+    cache_examples=False,
+)
 
-demo = gr.TabbedInterface([app1, app2], ["Classify", "Detect"])
+demo = gr.TabbedInterface([app1, app2,app3], ["Classify", "Detect","Video Interface"])
 
 
 # Launch the demo!