update

app.py

@@ -224,7 +224,7 @@ def llm_call(question_prompt, model_name,
     top_p=1, n_samples=64, stop=None):
     if HUGGINGFACE:
         model_inputs = hug_tokenizer([question_prompt], return_tensors="pt").to('cuda')
-        generated_ids = hug_model.generate(**model_inputs, max_length=1400, temperature=1, num_return_sequences=8, do_sample=True)
+        generated_ids = hug_model.generate(**model_inputs, max_length=1400, temperature=1, num_return_sequences=9, do_sample=True)
         responses = hug_tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
         codes = []
         for response in responses:

myturtle_cv.py

@@ -25,7 +25,7 @@ def crop_and_scaled_imgs(imgs):
     w = x_end - x
     h = y_end - y
 
-    SIZE = 400
+    SIZE = 300
     # Calculate the position to center the ROI in the SIZExSIZE image
     start_x = max(0, (SIZE - w) // 2)
     start_y = max(0, (SIZE - h) // 2)