Update script.py

script.py

@@ -1,32 +1,20 @@
+## load necessary modules and libaries
+import cv2
 import os
-from PIL import Image
-import pandas as pd
 
-def get_image_data(folder_path):
-    image_data = []
 
-    # Iterate through all files in the folder
-    for filename in os.listdir(folder_path):
-        file_path = os.path.join(folder_path, filename)
-        
-        # Check if the file is an image
-        if os.path.isfile(file_path) and filename.lower().endswith(('.png', '.jpg', '.jpeg', '.gif', '.bmp')):
-            try:
-                with Image.open(file_path) as img:
-                    width, _ = img.size
-                    image_data.append({'id': filename, 'pred': width})
-            except IOError:
-                print(f"Error opening {filename}. Skipping this file.")
-    
-    return image_data
+## Set Path to test images from folder (image shape is: 360x640x3)
+TEST_IMAGE_PATH = "/tmp/data/test_images"
+print()
+print(os.listdir(TEST_IMAGE_PATH))
+print()
 
-# Specify the folder path
-folder_path = "/tmp/data/data"
 
-# Get image data
-image_data = get_image_data(folder_path)
+## Set Path to your model weights (stored in your model directory)
+# MODEL_WEIGHTS_PATH = 'yolov5s.pt'
 
-# Create DataFrame
-df = pd.DataFrame(image_data)
+## load model
+#model = load_model(MODEL_WEIGHTS_PATH) # the load_model function needs to be created by yourself
 
-df.to_csv("solution.csv", index=False)
+## run inference on test images to create submission.csv file
+# run_inference(model, TEST_IMAGE_PATH) # the run_inference function needs to be created by yourself