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Runtime error
refactor: apply tqdm, global_dict func, add some info texts
Browse files- src/obs_eval_gradio.py +18 -6
src/obs_eval_gradio.py
CHANGED
@@ -94,7 +94,11 @@ def _make_video_batch(image_file, batch_size, total_batch_percent):
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# assert len(batch) <= BATCH_SIZE
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print(f'##{idx} - batch_size: {len(batch)}')
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-
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return base64FramesBatch
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@@ -118,13 +122,15 @@ def show_batches(image_file, batch_size, total_batch_percent):
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return images
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-
def call_gpt_vision(api_key, instruction):
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frames = global_dict.get('batched_frames')
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openai.api_key = api_key
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full_result = []
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-
for
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PROMPT_MESSAGES = [
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{
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"role": "system",
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@@ -151,7 +157,9 @@ def call_gpt_vision(api_key, instruction):
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full_result.append(result)
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except Exception as e:
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print(f"Error: {e}")
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-
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if 'full_result' not in global_dict:
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global_dict.setdefault('full_result', full_result)
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@@ -160,9 +168,11 @@ def call_gpt_vision(api_key, instruction):
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print(f'### BATCH_{idx+1}')
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print('-'*100)
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time.sleep(2)
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-
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def get_full_result():
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@@ -231,12 +241,14 @@ def main():
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)
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batch_size = gr.Number(
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label="Number of images in one batch",
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-
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minimum=2,
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maximum=5
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)
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total_batch_percent = gr.Number(
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label="Percentage(%) of batched image frames to total frames",
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value=5,
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minimum=5,
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maximum=20,
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# assert len(batch) <= BATCH_SIZE
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print(f'##{idx} - batch_size: {len(batch)}')
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if 'batched_frames' not in global_dict:
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global_dict.setdefault('batched_frames', base64FramesBatch)
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else:
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global_dict['batched_frames'] = base64FramesBatch
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return base64FramesBatch
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return images
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+
def call_gpt_vision(api_key, instruction, progress=gr.Progress()):
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frames = global_dict.get('batched_frames')
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openai.api_key = api_key
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full_result = []
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full_text = ""
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idx = 0
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for batch in progress.tqdm(frames):
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PROMPT_MESSAGES = [
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{
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"role": "system",
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full_result.append(result)
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except Exception as e:
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print(f"Error: {e}")
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full_text += f'### BATCH_{idx+1}\n' + "-"*50 + "\n" + f"Error: {e}" + "\n" + "-"*50 + "\n"
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idx += 1
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pass
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if 'full_result' not in global_dict:
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global_dict.setdefault('full_result', full_result)
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print(f'### BATCH_{idx+1}')
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print('-'*100)
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full_text += f'### BATCH_{idx+1}\n' + "-"*50 + "\n" + result.choices[0].message.content + "\n" + "-"*50 + "\n"
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idx += 1
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time.sleep(2)
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return full_text
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def get_full_result():
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)
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batch_size = gr.Number(
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label="Number of images in one batch",
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info="(2<=N<=5)"
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value=5,
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minimum=2,
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maximum=5
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)
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total_batch_percent = gr.Number(
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label="Percentage(%) of batched image frames to total frames",
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info="(5<=P<=20)"
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value=5,
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minimum=5,
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maximum=20,
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