Add application file

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+import numpy as np
+import cv2 
+import os,glob
+import json
+
+with gr.Blocks() as demo:
+    video_upload = gr.UploadButton(label="Upload the Video", file_types=["video"])
+    slider = gr.Slider(maximum=200,interactive=True,steps=1)
+    frames = []
+    def get_frame(video):
+        frames.clear()
+        files = glob.glob('frames/*')
+        for f in files:
+            os.remove(f)
+        cap = cv2.VideoCapture(video.name)
+        i = 0
+        for i in range(201):
+            ret, frame = cap.read()
+            if ret == False:
+                break
+            frames.append(frame)
+            # cv2.imwrite("frames/frame_{}.jpeg".format(i),frame)
+            i += 1
+        cap.release()
+        cv2.destroyAllWindows()
+    video_upload.upload(fn=get_frame, inputs=[video_upload])
+    def return_frame(index):
+        # img = cv2.imread("frames/frame_{}.jpeg".format(index))
+        img = frames[index]
+        return img
+    slider.change(return_frame,slider,gr.Image(shape=(1280, 720),type="numpy"))    
+    question = gr.Textbox(label="Question")
+    model_type = gr.CheckboxGroup(["SurgGPT","LCGN"],label="Model Choice")
+    answer = gr.Textbox(label="Answer")
+    predict = gr.Button(value="Predict")
+    def predict_ans(index,question,model_choice):
+        return "hi"
+    predict.click(fn=predict_ans,inputs=[slider,question,model_type],outputs=[answer])
+    
+if __name__ == "__main__":
+    demo.launch()