Upload app.py

app.py

@@ -1,18 +1,35 @@
 import gradio as gr
 import numpy as np
 from fish_feeding import FishFeeding
-
+import cv2
 model = FishFeeding()
 model.load_models()
 
-def fish_feeding(images):
-    for i, img in enumerate(images):
-        images[i] = np.array(img, dtype=np.uint8)
+  
+def FrameCapture(path): 
+  
+    # Path to video file 
+    vidObj = cv2.VideoCapture(path) 
+    success = 1
+    images = []
+    count = 0
+    while success: 
+
+            success, image = vidObj.read()
+        
+            if success and count % 3 == 0:
 
+                image= np.array(image, dtype=np.uint8)
+                images.append(image)
+            count += 1
+    return images      
+
+def fish_feeding(images):
+    images = FrameCapture(images)
     total_feed, times = model.final_fish_feed(images)
     return {"total_feed": total_feed, "times": times}
 
-inputs = gr.Image(type='numpy', label="Upload fish images")
+inputs = gr.Video(label="Upload fish images")
 outputs = gr.JSON(label="Fish Feeding Results")
 
 app = gr.Interface(fish_feeding, inputs=inputs, outputs=outputs, title="Fish Feeding Predictor")